Machining Engineer jobs at Nextdoor - 1891 jobs

The Offline Driving Intelligence team is responsible for developing Foundation Models for prediction and planning, applying them both off-vehicle to provide ML capabilities to simulation and validation and on-vehicle to influence driving models. Our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Prediction and Planning Machine Learning Engineer you will work on the bleeding edge of the industry, developing novel machine learning pipelines and models to predict the behavior of other agents in the world and planning the best course of action for the ego vehicle. In this role, you will: Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort, compliance. Contribute to our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field Develop metrics and tools to analyze errors and understand improvements of our systems Collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications PhD degree in Computer Science or related field +1 year of professional experience (top tier publications can remove the need for the year of experience) OR MSc +5y of professional experience in a relevant field. Experience in Planning and / or Prediction using Reinforcement Learning techniques Experience with training and deploying transformer-based model architectures Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in C++ or Fluency in Python with a basic understanding of C++ Bonus Qualifications Top tier publications (NeurIPS, ICML, CVPR) $214,000 - $257,000 a year Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign‑on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long‑term care insurance, long‑term and short‑term disability insurance, and life insurance. #J-18808-Ljbffr

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff-like payroll, health insurance, 401(k)s, and HR-so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we're proud to support more than 400,000 small businesses across the country, and we're building a workplace that represents and celebrates the customers we serve. Learn more about our Total Rewards philosophy . About the Role: Gusto's Data Science team leverages Gusto's rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers. For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem. You'll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you'll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world- class, high secure platform that safeguards our users' activities and money, and ensures unparalleled reliability. Here's what you'll do day-to-day: Build and deploy machine learning models to identify, assess and mitigate risks Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model's performance over time Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems Develop scalable frameworks and libraries that enhance and contribute to the team's core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights. Identify new opportunities to leverage data to improve Gusto's products and help risk management team to understand business requirements and develop tailored solutions Present and communicate results to stakeholders across the company Here's what we're looking for: 8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion PhD or Masters plus equivalent experience in a quantitative field is a plus Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $225,000 - $285,000 for San Francisco, New York, and Seattle, $205,000- $255,000 in Los Angeles, $187,000 - $235,000 in Denver, and $200,000 - $250,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Interested in building your career at Gusto, Inc.? Get future opportunities sent straight to your email. #J-18808-Ljbffr

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff-like payroll, health insurance, 401(k)s, and HR-so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we're proud to support more than 400,000 small businesses across the country, and we're building a workplace that represents and celebrates the customers we serve. Learn more about our Total Rewards philosophy . About the Role: Gusto's Data Science team leverages Gusto's rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers. For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem. You'll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you'll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world- class, high secure platform that safeguards our users' activities and money, and ensures unparalleled reliability. Here's what you'll do day-to-day: Build and deploy machine learning models to identify, assess and mitigate risks Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model's performance over time Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems Develop scalable frameworks and libraries that enhance and contribute to the team's core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights. Identify new opportunities to leverage data to improve Gusto's products and help risk management team to understand business requirements and develop tailored solutions Present and communicate results to stakeholders across the company Here's what we're looking for: 8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion PhD or Masters plus equivalent experience in a quantitative field is a plus Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $225,000 - $285,000 for San Francisco, New York, and Seattle, $205,000- $255,000 in Los Angeles, $187,000 - $235,000 in Denver, and $200,000 - $250,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Interested in building your career at Gusto, Inc.? Get future opportunities sent straight to your email. #J-18808-Ljbffr

Employment Type Full time Department Engineering Compensation Estimated Base Salary $220K - $320K • Offers Equity Help us build the systems that train specialized AI models for the fastest-growing companies in the world. If you love taking cutting‑edge ML techniques and turning them into products that ship, we'd love to meet you. About Inference.net Inference.net trains and hosts specialized language models for companies who want frontier-quality AI at a fraction of the cost. The models we train match GPT‑5 accuracy but are smaller, faster, and up to 90% cheaper. Our platform handles everything end‑to‑end: distillation, training, evaluation, and planet‑scale hosting. We are a well‑funded ten‑person team of engineers who work in‑person in downtown San Francisco on difficult, high‑impact engineering problems. Everyone on the team has been writing code for over 10 years, and has founded and run their own software companies. We are high‑agency, adaptable, and collaborative. We value creativity alongside technical prowess and humility. We work hard, and deeply enjoy the work that we do. Most of us are in the office 4 days a week in SF; hybrid works for Bay Area candidates. About the Role You will be responsible for building and improving the core ML systems that power our custom model training platform, while also applying these systems directly for customers. Your role sits at the intersection of applied research and production engineering. You'll lead projects from data intake to trained model, building the infrastructure and tooling along the way. Your north star is model quality at scale, measured by how well our custom models match frontier performance, how efficiently we can train and serve them, and how smoothly we can deliver results to our customers. You'll own the full training lifecycle: processing data, creating dashboards for visibility, training models using our frameworks, running evaluations, and shipping results. This role reports directly to the founding team. You'll have the autonomy, a large compute budget / GPU reservation, and technical support to push the boundaries of what's possible in custom model training. Key Responsibilities Lead projects from data intake through the full training pipeline, including processing, cleaning, and preparing datasets for model training Build and maintain data processing pipelines for aggregating, transforming, and validating training data Create dashboards and visualization tools to display training metrics, data quality, and model performance Train models using our internal frameworks and iterate based on evaluation results Develop robust benchmarks and evaluation frameworks that ensure custom models match or exceed frontier performance Build systems to automate portions of the training workflow, reducing manual intervention and improving consistency Take research features and ship them into production settings Apply the latest techniques in SFT, RL, and model optimization to improve training quality and efficiency Collaborate with infrastructure engineers to scale training across our GPU fleet Deeply understand customer use cases to inform training strategies and surface edge cases Requirements 2+ years of experience training AI models using PyTorch Hands‑on experience with post‑training LLMs using SFT or RL Strong understanding of transformer architectures and how they're trained Experience with LLM‑specific training frameworks (e.g., Hugging Face Transformers, DeepSpeed, Axolotl, or similar) Experience training on NVIDIA GPUs Strong data processing skills and comfortable building ETL pipelines and working with large datasets Track record of creating benchmarks and evaluations Ability to take research techniques and apply them to production systems Nice‑to‑Have Experience with model distillation or knowledge transfer Experience building dashboards and data visualization tools Familiarity with vision encoders and multimodal models Experience with distributed training at scale Contributions to open‑source ML projects You don't need to tick every box. Curiosity and the ability to learn quickly matter more. Compensation We offer competitive compensation, equity in a high‑growth startup, and comprehensive benefits. The base salary range for this role is $220,000 - $320,000, plus equity and benefits, depending on experience. Equal Opportunity Inference.net is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status. If you're excited about building the future of custom AI infrastructure, we'd love to hear from you. Please send your resume and GitHub to ****************** and/or apply here on Ashby. Compensation Range: $220K - $320K #J-18808-Ljbffr

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff-like payroll, health insurance, 401(k)s, and HR-so owners can focus on their craft and customers. With teams in Denver, San Francisco, and New York, we're proud to support more than 400,000 small businesses across the country, and we're building a workplace that represents and celebrates the customers we serve. Learn more about our Total Rewards philosophy . About the Role: Gusto's Data Science team leverages Gusto's rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers. For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem. You'll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you'll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world- class, high secure platform that safeguards our users' activities and money, and ensures unparalleled reliability. Here's what you'll do day-to-day: Build and deploy machine learning models to identify, assess and mitigate risks Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model's performance over time Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems Develop scalable frameworks and libraries that enhance and contribute to the team's core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights. Identify new opportunities to leverage data to improve Gusto's products and help risk management team to understand business requirements and develop tailored solutions Present and communicate results to stakeholders across the company Here's what we're looking for: 8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion PhD or Masters plus equivalent experience in a quantitative field is a plus Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $225,000 - $285,000 for San Francisco, New York, and Seattle, $205,000- $255,000 in Los Angeles, $187,000 - $235,000 in Denver, and $200,000 - $250,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Interested in building your career at Gusto, Inc.? Get future opportunities sent straight to your email. #J-18808-Ljbffr

At Pave, we're building the industry's leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision. Top tier companies like OpenAI, McDonald's, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 58% of Forbes AI 50 use Pave to benchmark compensation. The future of pay is real-time & predictive, and we're making it happen right now. We've raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures. Research & Design Org Pave's R&D pillar includes our data science, engineering, information technology, product design, product management, and security teams. This organization builds, maintains, and secures a platform used by more than 8,500+ client organizations. Our engineering team moves between ideation, scoping, and execution in a matter of days while closely iterating with cross‑functional partners on requirements. At Pave, we use TypeScript, Node.js, and React, hosted on GCP. Compensation strategy is broken down into three pillars - compensation bands, planning workflows, and total rewards communication. We build products that make these processes seamless for customers. Over the next year, our roadmap is focused on enhancing the entire compensation lifecycle: from philosophy definition to market trend analysis, band adjustments, merit cycles, and employee communication. We're seeking passionate engineers who are excited about building robust, data‑rich systems that simplify complex compensation processes at scale. The Data Team @ Pave As part of the Data team at Pave, you will help us redefine how companies understand the labor market and determine compensation. Even the most innovative tech companies in the world often use spreadsheets full of flawed statistics to determine how to pay. At Pave, we've built a system of real‑time integrations that allow us to bring best practices from machine learning, data science, software tooling, and AI to an industry that is built on data, but doesn't have the tools it needs to fully leverage it. What You'll Do Architect and implement scalable ML systems for modeling compensation within a single company and across the market as a whole Collaborate with product and engineering teams to identify additional opportunities to leverage ML‑driven solutions Help evolve the technical direction of ML initiatives across the company Drive millions of dollars of revenue growth What You'll Bring 5+ years of experience building and deploying ML models in production environments Strong foundation in machine learning, statistics, and deep learning fundamentals Expertise in Python and modern ML frameworks (PyTorch, TensorFlow, or similar) Experience with large‑scale data processing and ML model optimization Experience with MLOps practices and tools (model versioning, monitoring, and deployment) Strong software engineering practices and experience with production systems Expert‑level SQL skills with experience writing complex queries and optimizing query performance Ability to navigate (and bring structure to) ambiguity; ability to bring a project from 0 to 1, or scale a project from 1 to 100 Compensation Salary is just one component of Pave's total compensation package for employees. Your total rewards package at Pave will include equity, top‑notch medical, dental, and vision coverage, a flexible PTO policy, and many other region‑specific benefits. Your level is based on our assessment of your interview performance and experience, which you can always ask the hiring manager about to understand in more detail. This salary range may include multiple levels. The targeted cash compensation for this position is (level depends on experience and performance in the interview process): P3: $195,000 - $215,000 P4: $230,000 - $250,000 Life @ Pave Since being founded in 2019, Pave has established a robust global footprint. Headquartered in San Francisco's Financial District, we operate strategic regional hubs across New York City's Flatiron District, Salt Lake City, and the United Kingdom. We cultivate a vibrant, collaborative workplace culture through our hybrid model, bringing teams together in‑person on Mondays, Tuesdays, Thursdays, and Fridays to foster innovation and strengthen professional relationships. Benefits Complete Health Coverage: Comprehensive Medical, Dental and Vision coverage for you and your family, with plenty of options to suit your needs Time off & Flexibility: Flexible PTO and the ability to work from anywhere in the world for a month Meals & Snacks: Lunch & dinner stipends as well as fully stocked kitchens to fuel you Professional Development: Quarterly education stipend to continuously grow Family Support: Robust parental leave to bond with your new family Commuter Assistance: A commuter stipend to help you collaborate in person Vision & Mission Our vision is to unlock a labor market built on trust. Our mission is to build confidence in every compensation decision. Equal Employment Opportunity As set forth in Pave's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. #J-18808-Ljbffr

At Pave, we're building the industry's leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision. Top tier companies like OpenAI, McDonald's, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 58% of Forbes AI 50 use Pave to benchmark compensation. The future of pay is real-time & predictive, and we're making it happen right now. We've raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures. Research & Design Org Pave's R&D pillar includes our data science, engineering, information technology, product design, product management, and security teams. This organization builds, maintains, and secures a platform used by more than 8,500+ client organizations. Our engineering team moves between ideation, scoping, and execution in a matter of days while closely iterating with cross‑functional partners on requirements. At Pave, we use TypeScript, Node.js, and React, hosted on GCP. Compensation strategy is broken down into three pillars - compensation bands, planning workflows, and total rewards communication. We build products that make these processes seamless for customers. Over the next year, our roadmap is focused on enhancing the entire compensation lifecycle: from philosophy definition to market trend analysis, band adjustments, merit cycles, and employee communication. We're seeking passionate engineers who are excited about building robust, data‑rich systems that simplify complex compensation processes at scale. The Data Team @ Pave As part of the Data team at Pave, you will help us redefine how companies understand the labor market and determine compensation. Even the most innovative tech companies in the world often use spreadsheets full of flawed statistics to determine how to pay. At Pave, we've built a system of real‑time integrations that allow us to bring best practices from machine learning, data science, software tooling, and AI to an industry that is built on data, but doesn't have the tools it needs to fully leverage it. What You'll Do Architect and implement scalable ML systems for modeling compensation within a single company and across the market as a whole Collaborate with product and engineering teams to identify additional opportunities to leverage ML‑driven solutions Help evolve the technical direction of ML initiatives across the company Drive millions of dollars of revenue growth What You'll Bring 5+ years of experience building and deploying ML models in production environments Strong foundation in machine learning, statistics, and deep learning fundamentals Expertise in Python and modern ML frameworks (PyTorch, TensorFlow, or similar) Experience with large‑scale data processing and ML model optimization Experience with MLOps practices and tools (model versioning, monitoring, and deployment) Strong software engineering practices and experience with production systems Expert‑level SQL skills with experience writing complex queries and optimizing query performance Ability to navigate (and bring structure to) ambiguity; ability to bring a project from 0 to 1, or scale a project from 1 to 100 Compensation Salary is just one component of Pave's total compensation package for employees. Your total rewards package at Pave will include equity, top‑notch medical, dental, and vision coverage, a flexible PTO policy, and many other region‑specific benefits. Your level is based on our assessment of your interview performance and experience, which you can always ask the hiring manager about to understand in more detail. This salary range may include multiple levels. The targeted cash compensation for this position is (level depends on experience and performance in the interview process): P3: $195,000 - $215,000 P4: $230,000 - $250,000 Life @ Pave Since being founded in 2019, Pave has established a robust global footprint. Headquartered in San Francisco's Financial District, we operate strategic regional hubs across New York City's Flatiron District, Salt Lake City, and the United Kingdom. We cultivate a vibrant, collaborative workplace culture through our hybrid model, bringing teams together in‑person on Mondays, Tuesdays, Thursdays, and Fridays to foster innovation and strengthen professional relationships. Benefits Complete Health Coverage: Comprehensive Medical, Dental and Vision coverage for you and your family, with plenty of options to suit your needs Time off & Flexibility: Flexible PTO and the ability to work from anywhere in the world for a month Meals & Snacks: Lunch & dinner stipends as well as fully stocked kitchens to fuel you Professional Development: Quarterly education stipend to continuously grow Family Support: Robust parental leave to bond with your new family Commuter Assistance: A commuter stipend to help you collaborate in person Vision & Mission Our vision is to unlock a labor market built on trust. Our mission is to build confidence in every compensation decision. Equal Employment Opportunity As set forth in Pave's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. #J-18808-Ljbffr

Strava is the app for active people. With over 150 million athletes in more than 185 countries, Strava is where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, we help you find your crew, crush your milestones, and keep moving forward. Start your journey with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. About This Role We are looking for a Senior Machine Learning Platform Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for developing sophisticated machine learning models and systems, plus leveraging generative AI technologies. Together this provides value to Strava athletes in various aspects including personalization, recommendations, search, and trust and safety. This is an important role on the team to develop and expand the platform behind the curtain. This lets us build models of higher quality with less friction. It helps ensure our models are served with stability and reliability, while ensuring we monitor model performance carefully. Ultimately you won't just help with the things we are doing now, but also unlock our technological capabilities for the future. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office- three days per week. What You'll Do: Own End to End Systems: Drive key projects to power AI/ML at Strava end-to-end from gathering stakeholders requirements to ground up developer to driving adoption and optimizing the experience Interact with a Rich and Large Dataset: Explore and help leverage Strava's extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features Contribute to a Well Loved Consumer Product: Work at the intersection of AI and fitness to help launch and maintain product experiences that will be used by tens of millions of active people worldwide You Will Be Successful Here By: Holding empathy and perspective: Work closely with engineers and data scientists to understand the opportunities to help them succeed; they will be your customers! Leading as an owner: Owning your work end-to-end and being accountable for the outcomes in the projects you lead, influencing the ML team, partner teams, and landing impact for the business. Ensure the end-to-end system delivers as expected through collaboration with partners. Collaborating in and across teams: Build relationships, advocate and communicate with cross-functional partners and product verticals to identify opportunities and bring your technical vision to life. Driving innovation with product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate, and gain buy-in for innovative techniques to enhance our existing platform, resulting in step-function changes to how we build AI at Strava. Being passionate about the work you are doing and contributing positively to Strava's inclusive and collaborative team culture and values What You'll Bring to the Team: Have worked on complex, ambiguous platform challenges and broken them down into manageable tasks with both strategies and tactical execution. Demonstrated technical leadership in leading projects and the ability to mentor and grow early-career team members. Have demonstrated strong interpersonal and communication skills, and a collaborative approach to drive business impact across teams. Have worked with a variety of MLOps tools that fulfill different ML needs (like FastAPI, LitServe, Metaflow, MLflow, Kubeflow, Feast) Are experienced in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing Experience with generative AI technologies around LLM evaluation, vector stores, and agent frameworks. Have built backend production tools and services on cloud environments like (but not limited to) AWS, using languages Python, Terraform, and other similar technologies. Have built and worked on data pipelines using large scale data technologies (like Spark, SQL, Snowflake) Have experience building, shipping, and supporting ML models in production at scale Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, Sagemaker For more information on benefits, please click here. Why Join Us? Movement brings us together. At Strava, we're building the world's largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you're shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you're not just joining a company-you're joining a movement. If you're ready to bring your energy, ideas, and drive, let's build something incredible together. Strava builds software that makes the best part of our athletes' days even better. Just as we're deeply committed to unlocking their potential, we're dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We're backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we're expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. #J-18808-Ljbffr

Our team is passionate about solving big challenges in healthcare and transforming the field of pathology with artificial intelligence. PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials. Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. Where You Fit We are seeking Machine Learning Engineers (MLE II, and III) to join our team and tackle unique machine learning challenges to advance medicine and improve patient care. You will work closely with teams across biomedical data science, product development, translational research, MLOps, and platform engineering to develop and deploy machine learning models for our AI products and services. What You'll Do As an MLE at PathAI, your responsibilities will grow in scope as you progress through levels: Design, develop, and deploy machine learning models for research and product development projects. Collaborate cross-functionally with scientists, engineers, and product teams to translate biological and clinical requirements into scalable ML solutions. Contribute to experimental design and analysis, including ideation, documentation, and reporting. Participate in knowledge sharing and team initiatives (e.g., design reviews, journal clubs, ML best practices, governance activities). Improve ML pipelines and infrastructure in partnership with MLOps and platform teams. Publish and present scientific work, supporting abstracts, manuscripts, and conference contributions. Level-specific expectations: MLE I: Contribute to projects with guidance, implement models, and learn best practices. MLE II: Independently deliver on projects, improve processes, and mentor junior engineers. MLE III: Lead initiatives end-to-end, set technical direction, and identify new opportunities with clear business and scientific impact. You will have the opportunity to work in a company where all employees put patients first. We believe that every team member provides valuable contributions to our success, and no task is too small for anyone if it's important to our company goals. Every PathAI employee is a contributor to our mission to pioneer better patient care by providing the best, most innovative AI tools to biotech, pathologists, clinicians and healthcare organizations. You will work alongside and with leading innovators in the field of AI and medicine and you will play a critical role in product development to impact patient outcomes. What You Bring We welcome applicants across all MLE levels. Minimum qualifications differ by level: MLE II: Master's degree plus 2-4 years of experience, or Ph.D. with 0-2 years of experience. Proven track record of developing and deploying machine learning models into production or research applications. Strong proficiency in Python, ML frameworks, and data pipeline development. Demonstrated ability to work independently on projects, contribute to experimental design, and improve ML workflows. Strong communication skills and ability to collaborate across scientific and engineering teams. MLE III Master's degree plus 5+ years of experience, or Ph.D. with 3+ years of experience. Deep expertise in ML, computer vision, or biomedical AI, with a history of high-impact contributions (publications, open-source, or products). Mastery of ML frameworks, software engineering best practices, and deployment pipelines. Ability to lead end-to-end projects, mentor others, and set technical direction. Experience articulating technical improvements into business or clinical impact. Strong record of contributions to scientific strategy (abstracts, manuscripts, conference presentations). We Want To Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for. PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications - that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. The cash compensation outlined below includes base salary or hourly wage and on-target commission for employees in eligible roles. The summary below indicates if an employee in this position is eligible for annual bonus, overtime pay and equity awards. Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors. #J-18808-Ljbffr

About Treering Treering, a Silicon Valley-based tech company, helps people preserve and celebrate their memories. By combining just-in-time digital printing with the power of AI tools, Treering delivers personalized keepsakes that celebrate important milestones and events. About the Role We are seeking a highly skilled AI Engineer to lead the maintenance and enhancement of our existing AI solutions. This role will be crucial in ensuring the smooth operation and continuous improvement of our AI-driven product generation process. You will be working with a suite of APIs designed to analyze, score, and rank photos, making critical decisions to automatically generate photobooks, yearbooks, and other print-on-demand products. Responsibilities AI Systems Maintenance: Maintain and optimize existing AI solutions, including APIs for photo analysis, scoring, and ranking. Enhancement and Development: Develop and enhance AI models and algorithms to improve the accuracy and efficiency of automated product generation. API Management: Oversee and manage the suite of APIs used in our AI solutions. Cloud Infrastructure: Utilize and manage AWS services such as Rekognition, Lambda, SageMaker, Step Functions, SQS, OpenSearch, S3, and RDS. State Machine Management: Design, implement, and manage state machines for orchestrating AI processes. Programming: Write and maintain Python code for AI models and API development. Monitoring and Troubleshooting: Monitor AI system performance, troubleshoot issues, and implement solutions. Collaboration: Work closely with cross-functional teams to integrate AI solutions into the overall product workflow. What We're Looking For Bachelor's or higher degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 6+ years of experience in AI development and deployment. Strong proficiency in Python programming. Extensive experience with AWS services, including Rekognition, Lambda, SageMaker, Step Functions, State Machines, SQS, OpenSearch, S3, and RDS. Experience with API development and management. Solid understanding of machine learning algorithms and techniques. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Strong leadership and mentoring abilities. Why Join Treering? Impact: Your work directly contributes to modernizing the yearbook industry. Innovation: Work with cutting-edge technologies in an agile environment. Growth: Opportunities for career advancement and professional development. Culture: A collaborative, inclusive, and supportive team environment. Benefits Comprehensive medical, dental, vision, life/AD&D, and disability coverage Pre-tax savings/spending plans, including HSA employer contributions Parental Leave Benefits Pre-tax and Roth 401(k) plan with an employer contribution Flexible vacation for salaried Twelve paid holidays throughout the year $180,000 - $200,000 a year If you are an experienced software engineer who thrives in a dynamic environment and is passionate about designing and implementing innovative web solutions, we invite you to apply. #J-18808-Ljbffr

DataVisor is a next generation security company that utilizes industry leading unsupervised machine learning to detect fraudulent activity for financial transactions, mobile user acquisition, social networks, commerce and money laundering. Our solution is used by some of the largest internet properties in the world, including Pinterest, Synchrony Financial, AirAsia and PingAn, to protect them from the ever-increasing risk of fraud. Our award-winning software is powered by a team of world‑class experts in big data, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us! The modeling / data science team holds the secret sauce of DataVisor. We run our advanced core unsupervised analytics engine and machine learning models on hundreds of billions of events from hundreds of millions of users. We are a mix of machine learning engineers and inquisitive data scientists. We love finding beautiful patterns in big data to catch and prevent malicious attacks against good users. We're also not afraid to get our hands dirty; we get deep satisfaction coming up with and implementing new ideas for improvements to our detection engine. If you have a knack for wrangling big data, are excited by the idea of being part of new technological frontiers, and want to work on a team that impacts the company's bottom line, we'd love to talk to you. 2+ years experience with Java/C++ Familiar with common data structures and algorithms. Be able to write efficient and optimized computer programs 1+ years experience with web backend or Hadoop/MapReduce/Spark 1+ years experience with machine learning/data science preferred Anti‑fraud modeling in financial industry a plus Bachelor degree required, Master/PhD degree preferred We offer a flexible schedule with competitive pay, equity participation and health benefits, along with catered lunch, company off‑sites, and game nights, as well as the opportunity to work with a world class team. #J-18808-Ljbffr

At Quantcast, we're redefining what's possible in digital advertising. As a global Demand Side Platform (DSP) powered by AI, we help marketers connect with the right audiences and deliver measurable results across the Open Web. Our foundation is built on cutting-edge measurement and consumer analytics, giving our clients the tools they need to drive success in an ever-evolving digital landscape. Since our start in 2006, we've pioneered industry firsts-from launching the original measurement platform for digital publishers to introducing the first AI-driven DSP. If you're ready to be part of a dynamic, forward-thinking team that thrives on creating transformative solutions, Quantcast is the perfect place to grow your career. The Modeling team is responsible for Machine Learning (ML) systems at Quantcast. We build and maintain multiple ML products that price millions of bid requests per second in a real-time auction environment to maximize advertiser outcomes. For each bid our models predict age, gender, viewability, fraud, advertiser relevance and many more characteristics. We are developing novel and effective platforms and algorithms to combine our vast first-party dataset with third-party data to provide the highest quality demographic and behavioral analysis of digital audiences on the market. As a Staff Machine Learning Engineer, you will use our large datasets, computational power, and analytic tools to build high quality and diverse products to support Quantcast's position as a leader in advertising. You will help lead our efforts in crafting, implementing, and operating large-scale machine learning systems in a production environment. You care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof of concepts, and build out scalable real-time production systems to tackle challenges the company faces. What you'll do: Design, code, test, and debug ML applications and constantly improve large-scale global systems that respond to millions of real-time requests per second efficiently. Prototype solutions, conduct data analyses to tackle large-scale inference problems, and run ML experiments to test new modeling ideas. Write clean, efficient, and maintainable code using industry best practices. Work multi-functionally with other teams to develop standard methodologies in model building and validation, and collaborate closely with engineering teams to deliver high-quality ML products. Identify performance bottlenecks and optimize system components for enhanced scalability. Mentor machine learning engineers to grow their careers and improve their skills, including participating in code reviews and providing constructive feedback to team members. Generate and review proposals for further research and development directions. Keep up to date with developments in machine learning outside the company. Who you are: M.S in Computer Science or related technical field with 8+ years of industry experience or Ph.D. with 5+ years, or equivalent practical experience. You must be work-authorized in the United States without the need for employer sponsorship. This is a hybrid role based in our San Francisco office. To ensure a manageable commute for in‑office days, candidates must reside within a 60-mile radius of San Francisco, CA. No relocation candidates at this time. Fluency in Python, Java, or similar object‑oriented programming language. Proficiency with ML algorithms such as classification, control systems, optimization, clustering, LLMs, or recommendation systems. An interest in distributed system and software design, concurrent algorithms, data structures, and software engineering. Solid foundation in math, statistics, data visualization, and storytelling. Demonstrated analytical, planning, and social skills. Experience coaching and developing junior machine learning engineers. The salary range for this position is $220,200 - $255,900. At Quantcast, we craft offers that reflect your unique skills, expertise, and geographic location. On top of a competitive salary, this position includes eligibility for a performance bonus, equity, and a comprehensive benefits package. Depending on your location, this may include generous vacation, medical, dental, and vision coverage, and retirement plans. For more details, visit our Careers page and see how we support our team. Please see the Applicant Privacy Notice for details on our applicant privacy policy. Founded in 2006 and headquartered in San Francisco, we are a diverse, aligned community with offices across 10 countries worldwide. Join the team that unlocks potential. Quantcast is an Equal Opportunity Employer. #J-18808-Ljbffr

The Public Sector ML team at Scale deploys advanced AI systems-including LLMs, agentic models, and multimodal pipelines-into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions. You will: Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge-based evaluations. Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes. Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing. Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes. Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems. Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases. Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets. This role will require an active security clearance or the ability to obtain a security clearance. Ideally you'd have: Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings. Strong programming skills in Python; experience with TensorFlow or PyTorch. Background in algorithms, data structures, and object-oriented programming. Experience with LLM pipelines, simulation environments, or automated evaluation systems. Ability to convert research insights into measurable evaluation criteria. Nice to haves: Graduate degree in CS, ML, or AI. Cloud experience (AWS, GCP) and model deployment experience. Experience with LLM evaluation, CV robustness, or RL validation. Knowledge of interpretability, adversarial robustness, or AI safety frameworks. Familiarity with ML evaluation frameworks and agentic model design. Experience in regulated, classified, or mission-critical ML domains. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$208,000-$300,000 USDPlease reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado is:$187,000-$270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

As the Smart Contract Engineer, you will build a Preconfirmation Registry and smart contracts of Based Appchain Framework with team. Responsibilities Implementation of Rollup smart contracts in Solidity Take engineering projects from design to production while working with our developers to manage realistic roadmaps You may have the opportunity to participate and talk in an event, conference or podcast Requirements Enthusiasm for the modular and rollup ecosystem Proficiency with Solidity and/or Rust and competent with VMs. Experience shipping and taking engineering projects to production Nice to have A deep understanding of fraud proofs and other rollup details Familiarity with the AggLayer, Espresso, and other modular products. A deep understanding of shared sequencing Understanding of ZK and DA Benefits Unlimited vacation policy Fully remote with flexible hours Competitive salary + equity package Regular team off-sites to international locations Work alongside the brightest minds in the crypto space Top-tier health, dental, and vision coverage for US employees Spire culture We play to win We work with authenticity We do what excites us the most We iterate rather than seek perfection We focus on the long-term goal that compounds #J-18808-Ljbffr

A leading technology company is seeking a Smart Contract Engineer to join their remote team. You will be tasked with implementing innovative smart contracts and managing project roadmaps, all while enjoying the flexibility of remote work and a competitive salary. This role offers the chance to work with talented individuals in the thriving crypto space, with benefits including unlimited vacation and top-tier health coverage. #J-18808-Ljbffr

Are you ready to join a growth-oriented team where creativity meets innovation? At Ware Malcomb, we are a dynamic and forward-thinking design firm committed to pushing the boundaries. Our team-oriented, collaborative approach ensures that every project is a blend of visionary design and seamless project delivery, and we are actively engaged with both the community and the industry. Discover our vibrant culture to get an inside look into life at Ware Malcomb and the programs we offer. Life at Ware Malcomb. As a Project Engineer at Ware Malcomb, you will support the delivery of innovative mechanical engineering projects from concept through construction. You will assist in preparing mechanical design reports and calculations, perform code research, develop complete sets of construction documents, and provide construction services such as site visits. This is a great opportunity to collaborate with clients, consultants, contractors, and our dynamic team while advancing your career in mechanical engineering. Responsibilities Complete computer and hand calculations supporting the mechanical design utilizing the applicable building and material codes while maintaining a high level of accuracy and attention to detail throughout all phases of the project. Prepare and oversee the development of models, calculation packages, construction documents, and specifications. Collaborate with Project Managers, Senior Project Managers and department managers to plan project layouts and integrate mechanical elements into cohesive designs. Participate in internal and external project meetings, coordinating with other disciplines. Conduct field work including site verifications, assessments, and troubleshooting. Perform construction administration duties, including periodic site visits to ensure compliance with design intent. Support the development and maintenance of engineering standards. Participate in quality assurance and quality control process within the team. Mentor the team in the use of mechanical calculation software and assist in task organization. Lead and coordinate mechanical engineering projects as Engineer of Record (EOR) when assigned. Conduct peer reviews and prepare reports on findings. Qualifications Bachelor's degree in Mechanical Engineering from an ABET-accredited program Professional Engineer (PE) license required 5+ years of experience in a mechanical engineering role Proficiency in Revit required Experience in Plumbing and Fire Protection design is highly preferred Strong communication, organizational, and analytical skills Ability to manage multiple priorities and provide technical guidance to team members Ability to provide timely, dependable, and professional service in a fast-paced environment Strong grasp of advanced financial concepts, with proven ability to perform intermediate calculations and conduct in-depth financial analysis Compensation: $100,000 - $135,000 a year. Read more about Life at Ware Malcomb. The final agreed upon compensation is based on individual education, qualifications, experience, licensing, project specialty/complexity and work location. At Ware Malcomb, certain roles are bonus eligible. Established in 1972, Ware Malcomb is a dynamic, forward-thinking commercial real estate design firm providing professional architecture, planning, interior design, civil engineering, branding, building measurement, structural engineering and MEP services to clients throughout the world. With office locations throughout the United States, Canada, Mexico and Brazil, the firm specializes in the design of office, industrial, science & technology, healthcare, multifamily, retail, and public/institutional projects. For six consecutive years, Ware Malcomb has been ranked as the #1 Industrial Sector Architecture Firm by Building Design + Construction Magazine. The firm is also ranked among the top 10 Architecture/Engineering firms in Engineering News-Record\'s Top 500 Design Firms and the Top 30 Interior Design Firms in Interior Design magazine\'s Top 100 Giants. For more information, visit Ware Malcomb.com. #J-18808-Ljbffr

A cutting-edge startup is seeking a Senior Mechanical Engineer in San Francisco to design and develop robotic components for cell therapy manufacturing. You will lead projects from conception to production using CAD and collaborate with cross-functional teams. Ideal candidates have extensive mechanical design experience, especially in bioprocess consumables or medical devices. The position offers a competitive salary and benefits, including health insurance and flexible PTO. #J-18808-Ljbffr

Nimble is an AI robotics company building the autonomous supply chain to enable fast, efficient, and sustainable commerce. We're developing a general-purpose robot AI and a warehouse generalist superhumanoid robot, the first robot in the world capable of performing all core warehouse functions. We recently closed a $106M Series C at a $1B valuation, and we are continuing to grow our world‑class team. Mission: to empower and inspire mankind to accomplish legendary feats by inventing robots that liberate us from the menial. Vision: invent the Autonomous Supply Chain - everything from the inside of factories and warehouses to your front door - powered by industry‑generalist superhumanoids to deliver faster, more efficient, and more sustainable commerce. Proudly led by founders from Stanford and Carnegie Mellon and a board featuring Marc Raibert (founder of Boston Dynamics), Sebastian Thrun (founder of GoogleX, Waymo), and Fei‑Fei Li (Chief Scientist of AI at Google). Join us and leave your mark on the future of robotics, AI, and global commerce. Core Values Be relentlessly resourceful - Challenge conventions and overcome obstacles. Be legendary - Be the very best and do work that inspires. Be humble - Prioritize growth, learning, and doing whatever is needed to further the mission. Be dependable - Take ownership and deliver with high agency. About the Role You will own the development and architecture of our next‑generation robotics diagnostic system, which is crucial for improving the reliability and maintainability of the robotic fleet. This system must proactively detect and surface anomalies across the entire robot stack-from low‑level firmware glitches to complex hardware failures-either automatically during operation or upon manual trigger. You will be the architect of the diagnostic data structure, translating complex sensor readings and error logs into actionable, easy‑to‑read health reports that accelerate root cause analysis for engineering, manufacturing, and support teams. This role requires tight collaboration with our Embedded Software and Infrastructure teams, and the Operations team to build a robust, scalable data pipeline. Key Responsibilities Design, implement, and maintain the on‑robot diagnostic framework, enabling both autonomous background checks and on‑demand manual diagnostic scans. Define the diagnostic data schema, ensuring efficient, standardized, and human‑readable reporting of fault codes, event logs, and status checks. This data structure must be scalable and optimized for use by both on‑robot systems and cloud‑based analytics tools. Work closely with embedded software and hardware teams to develop sophisticated diagnostic routines that surface hardware issues, abnormal sensor behavior (e.g., drift, noise, and communication failures), motor anomalies, and transient firmware glitches. Collaborate with the Infrastructure team to architect and build the data pipeline responsible for reliably collecting, storing (e.g., S3 or data lake), and processing high volumes of diagnostic data from the robot fleet. Ensure diagnostics generate clear, prioritized, and contextualized reports that summarize the state of the robot, enabling engineers to quickly understand the root cause of an abnormality without extensive log diving. Qualifications BS or MS in Computer Science, Electrical Engineering, Robotics, or a related technical discipline. 3+ years of professional experience in developing diagnostics, monitoring, or telemetry systems for complex electro‑mechanical devices, robotics, or embedded systems. Proficiency in software development (e.g., C++, Python) with specific experience in writing testable, robust code for embedded environments or robotics middleware. Experience with data structuring, schema design, and working with data ingestion pipelines (e.g., utilizing message queues, time‑series databases, or cloud data storage). Deep understanding of common robotics hardware and firmware failure modes, including motor control systems, sensor interfaces (e.g., CAN, I2C, Serial, USB), and power management systems. Technical triaging skills, familiarity with Ishikawa diagram are big plus. Familiarity with interpreting hardware schematics and leveraging low‑level system logs to identify failure points. Salary and Equity $145,000 - $190,000 a year. The range above is the salary range. This position will also receive generous equity. Culture We embrace challenges and strive to make the impossible possible each day. We're not in this to do what's easy or to be mediocre. We want to create something legendary and leave our mark on the world. We're ambitious, we're gritty, we're humble and we're relentlessly resourceful in pursuit of our goals. If this sounds like you then you might be a great fit! Nimble Robotics, Inc. is an equal opportunity employer. We make all employment decisions based solely on merit. We provide equal employment opportunity to all applicants and employees without discrimination on the basis of race, color, religion, national origin, ancestry, disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, sexual orientation, age, military or veteran status, or any other characteristic protected by applicable state, federal or local laws. Nimble's Benefits Paid Time Off - Enjoy the time you need to travel, rejuvenate, and connect with friends and family. Health Insurance - Nimble provides medical, dental, and vision insurance through several premier plans and options to support you and your family. Paid Parental Leave - Enjoy paid bonding time following a birth. Commuter Benefits - Take the stress out of commuting with access to fully‑paid parking spots. Referral Bonus - Get a cash bonus for any friend or colleague that you refer to us that we end up hiring. 401k - Contribute towards a 401k for retirement planning. Equity - Be an owner in Nimble through our equity program. #J-18808-Ljbffr

Job Description#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors At Nextdoor, Machine Learning is one of the most critical teams we are growing. ML is transforming our product through personalization, driving significant impact across various platform components, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great machine learning engineers who believe in the power of the local community to empower our members to make their communities great places to live. At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in-office presence and work-from-home experience for our valued employees. The Impact You'll Make You will be part of an avid and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis. Build and iterate on ML-driven products to foster creativity, discovery, and engagement on Nextdoor Develop personalized content and user recommendation systems that millions of users rely on daily Run and analyze live user-facing experiments to iterate on model quality Collaborate with other engineers and data scientists to create optimal experiences on the platform Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises Build in-person relationships with team members and contribute to Nextdoor's company culture We have MLE positions across multiple tracks, including Feed, Notifications, Ads, Network Growth, Knowledge Graph, and ML Platform. What You'll Bring To The Team Master's Degree or Ph.D. in Computer Science, Applied Math, Statistics, or a related field, graduating in December 2025/May-June 2026 Deep understanding of machine learning concepts (e.g. deep learning) and applications (e.g. recommender systems, knowledge graph) Internship in machine learning engineering in a related field (e.g. social networking, e-commerce) Strong programming skills in Python or Java Effective communication and collaboration skills Passion for Nextdoor's mission and purpose Bonus Points - Industry experience of applying machine learning at scale Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography. The starting salary for this role is expected to be $150,000 to $175,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date. Perks & Benefits We've got you covered! We are dedicated to supporting your personal and professional growth with a comprehensive benefits package that includes: Access to benefits (including mental health benefits, commuter benefits, wellness benefits, gender affirming care, etc) Flexible paid time off Dedicated volunteer days Stocked micro-kitchens and lunches at our offices Ability to join any of our Employee Resource Groups (ERGs) At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.