Mechanical design engineer jobs in Gilroy, CA

Mechanical Engineer (Robotics) We are partnering with a robotics company building complex electro-mechanical systems where mechanical design directly determines real-world performance. This role is for someone who doesn't just design parts, but owns motion, reliability, and scale. What You'll Do Own the end-to-end mechanical design of complex electro-mechanical systems with moving parts Design and prototype custom mechanisms and actuators under aggressive timelines Drive concepts from first prototype through high-volume production Personally design parts for volume manufacturing processes, including: Injection molding Die casting Stamping / sheet metal Extrusion Powder metal / MIM Partner closely with contract manufacturers (CMs) to ensure DFM, reliability, and cost targets are met Build systems that are not just elegant but robust, testable, and shippable at scale What We're Looking For Exceptionally strong mechanical intuition, you understand how things move, fail, and improve Proven ability to design and prototype quickly without sacrificing rigor Track record of shipping reliable, hardware products at scale Deep hands-on experience designing custom mechanisms, joints, transmissions, and actuators Experience owning mechanical architecture for complex systems with dynamic loads and tight tolerances Comfortable operating across ambiguity, tight timelines, and high expectations Required Background Currently working at a robotics company (hands-on mechanical role) Background in electro-mechanical systems with real moving parts (not CAD-only work) Experience taking designs from concept → prototype → volume production Ideal Signals Designed robotic arms, legs, mobile platforms, end-effectors, or actuation systems Personally responsible for motor selection, gearing, kinematics, or load paths Close collaboration with electrical and controls teams Bias for execution and ownership over documentation and theory

Machine Learning Model Engineer - Samsung Ads Samsung Ads is an advanced advertising technology company in rapid growth that focuses on enabling advertisers to connect audiences from Samsung devices as they are exposed to digital media, using the industry's most comprehensive data to build the world's smartest advertising platform. Being part of an international company such as Samsung and doing business around the world means that we get to work on big, complex projects with stakeholders and teams located around the globe. We are proud to have built a world-class organization grounded in an entrepreneurial and collaborative spirit. Working at Samsung Ads offers one of the best environments in the industry to learn just how fast you can grow, how much you can achieve, and how good you can be. We thrive on problem-solving, breaking new ground, and enjoying every part of the journey. Machine learning lies at the core of the advertising industry, and this is no exception to Samsung Ads. At Samsung Ads, we are actively exploring the latest machine learning techniques to improve our existing systems and products and create new revenue streams. As a machine learning model engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact. You will work closely with and be supported by a talented engineering team and top-notch researchers to work on exciting machine learning projects and state-of-the-art technologies. You will be welcomed by a unique learning culture and creative work atmosphere. This is an exciting and unique opportunity to get deeply involved in envisioning, designing and implementing cutting-edge machine learning products with a fast growing team. Responsibilities Lead and deliver production-grade machine learning products from end to end to make Samsung Ads a key player in the mobile ads market. Design, develop and deploy state-of-the-art and scalable machine learning models to achieve different optimization goals, such as ads click (pCTR), app-install optimization, ROAS optimization, retention, etc. Research the latest machine learning technologies with industry trends, create prototypes of new ML solutions quickly, and deploy the solution into production. Analyze complex problems with massive advertising data, identify gaps, and propose and execute technical proposals. Closely work with different internal ML teams (e.g., ML platform, ML serving, and MLOps teams) to improve our codebase and product health. Closely work with cross-functional partner teams in global settings to deliver new ML features and solutions and achieve business objectives. Mentor junior engineers and provide technical guidance. Learn quickly and adapt to a fast-paced working environment. Experience Requirements: Master's or PhD degree in Computer Science or related fields. 4+ years of industry experience with a Master's degree or 2+ years of industry experience with a PhD degree. Solid theoretical background in machine learning and/or data mining. Proficiency in mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.). Hands-on experience with production-grade machine learning solutions. Experience with mainstream big data tools (e.g., MapReduce, Spark, Flink, Kafka, etc.). Extensive programming experience in Python, Go or other OOP languages. Familiarity with data structures, algorithms and software engineering principles. Proficiency in SQL and databases. Strong communication and interpersonal skills to drive cross-functional partnerships. Preferred Experience Requirements: Publications in top relevant venues (e.g., TPAMI, NeurIPS, ICML, ICLR, KDD, WWW, SIGIR, AAAI, IJCAI, etc.). Basic knowledge about Amazon Web Services (AWS). Experience with the advertising industry and real-time bidding (RTB) ecosystem. CALIFORNIA ONLY Compensation for this role is expected to be between $240,000 and $280,000. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

Analog/Mixed-Signal Verification Engineer San Jose, CA -On-site Full-time/Direct Hire Responsibilities Develop and implement mixed-signal verification and coverage plans for complex IC designs based on design architecture and specifications Design and develop verification testbenches using industry-standard verification languages and methodologies Write and execute test cases to verify mixed-signal circuits for functionality, performance, and reliability Review and analyze verification results, and provide feedback to design teams Collaborate with design and layout teams to identify and resolve design issues Develop new verification methodologies, tools, and techniques, ensuring scalability and portability Sign-off mixed signal designs in preparation for tapeout Write behavioral models from custom analog and mixed-signal circuits in SystemVerilog HDL Collaborate with circuit design teams to understand fine details of custom circuits Collaborate with Design Verification team to craft hooks into the behavioral models for effective verification Run various simulations and equivalence checks to ensure that the model matches closely with the custom circuits Write scripts and simple tools for automating repetitive tasks Optimize and refine models to ensure accuracy while maintaining efficient simulation performance Review and analyze verification results, and provide feedback to design team Document modeling techniques and results for internal and external dissemination Keep updated with industry trends in modeling techniques Requirements Bachelor's degree in Electrical Engineering and 5+ years of relevant industry experience or equivalent Strong understanding of analog and mixed-signal circuit design and verification principles Ability to write test plans, present results, and communicate clearly with multi-functional teams Have a familiarity with verification methodologies and tools: simulators, waveform viewers, execution automation, simulation time optimization, and coverage collection Familiarity with analog behavioral models is a plus Deep knowledge of Verilog/SystemVerilog with ability to write synthesize-able and behavioral code Deep knowledge of digital logic gates, clocking and state elements Deep knowledge of SPICE simulation, HDL simulation and logic equivalence tools Working understanding of analog circuit architecture such as ADC, DAC, LDO, Charge pump, etc. Have good programming skills and can write efficient programs or scripts in Perl, Python, and/or C Excellent debugging, problem-solving and analytical skills Strong communication and teamwork skills -- Vilayath Khan ************************** Manager-TA

Senior Machine Learning Engineer (LLM / Audio / Voice AI) $200,000-$300,000 + Equity San Francisco Bay Area (Relocation + Sponsorship Available for Exceptional Talent) Permanent Our client is a rapidly scaling AI startup operating at $1M+ ARR per employee, building the next generation of real-time voice automation. They're now hiring exceptionally talented (Doesn't matter the years of experience) ML Engineer to help push the boundaries of speech, audio, and LLM-driven systems. This role sits at the core of their product: Training LLMs and audio models Designing high-performance ML infrastructure Deploying models that must operate reliably under real-world, latency-sensitive conditions Work end-to-end - experimentation, evaluation, productionisation, and continuous improvement The environment is fast-paced, deeply technical, and highly collaborative, with 80%+ onsite time expected. This is a true startup role: long hours, high ownership and reward, fast iteration, and the chance to make outsized impact on a rapidly growing product used by hundreds of thousands of customers. They're looking for engineers with strong academic foundations and demonstrated technical excellence (advanced degrees or standout research/engineering experience), plus hands-on experience shipping ML systems in demanding environments. If you thrive in ambiguity, love building real-world AI systems, and want to help shape a high-velocity ML organisation from the ground up, this is the opportunity. Apply now or reach out for details or to explore the role confidentially.

Machine Learning Engineer/Researcher Salary: Up to $300k Base The Role First hire owning agentic video pipelines. Build routing, fine-tuning, and backend logic that powers a next-gen video co-pilot. High autonomy. No hand-holding. What You'll Own Agentic pipelines for video/image tasks Routing across open-source + external VLM/LLM providers Fine-tuning + post-training on targeted tasks Low-latency backend services for video understanding Turning product needs into shipped features Must-Haves 2+ years fine-tuning LLMs/VLMs Hands-on with video/image models Built agentic or multimodal applications Comfortable as the only specialist building the foundation

Lead Machine Learning Engineer - Generative AI for the Physical World A rare opportunity has emerged for a visionary Lead Machine Learning Engineer to build the core intelligence for a stealth-mode, well-funded AI company. This foundational leadership role is for someone passionate about teaching machines to understand and engineer the physical world, moving beyond language and into the complex domain of 3D geometry and physics. Why Join? This is a chance to define a new category of software from the ground up. You will have the autonomy to set the technical vision, build a world-class team, and solve fundamental AI challenges that directly impact how next-generation products are designed and built. You will be instrumental in creating the "brain" that powers a revolutionary platform. The Company My client is a pioneering startup developing a new class of generative AI. Their platform uses autonomous agents to design, test, and optimize complex physical systems, aiming to radically accelerate today's slow and manual engineering cycles. Backed by top-tier investors, the company is positioned to become a leader in the application of AI to advanced hardware design and manufacturing. The Role As the Lead Machine Learning Engineer, you will architect the company's entire ML strategy. You will lead the research and development of the core models that allow AI agents to perceive and reason about 3D geometry. Your primary focus will be on defining the technical roadmap, hiring and mentoring a high-performing team, and guiding the development of novel techniques in geometric deep learning and multimodal reasoning. The Essential Requirements Proven experience leading machine learning teams, setting technical direction, and mentoring senior engineers. Deep expertise in 3D perception, scene understanding, or geometric deep learning (e.g., from robotics, AV, AR/VR). A strong track record of architecting and deploying complex ML systems from research to production. Fluency with modern ML frameworks (e.g., PyTorch) and models for geometric data (GNNs, 3D CNNs, NeRFs). Ability to translate ambiguous product goals into a concrete technical roadmap and execute effectively. What Will Make You Stand Out A PhD in a relevant field such as Computer Science or Robotics. A background in mechanical, aerospace, or a related engineering discipline. Experience integrating perception models with LLMs or other agent-based systems. A history of publications in top-tier machine learning conferences. Benefits Up to $260,000 base Meaningful equity A key leadership role with the autonomy to shape the company's technical culture and direction. The opportunity to solve high-impact problems at the intersection of AI and engineering. If you are interested in this role, please apply with your resume through this site. SEO Keywords for Search Head of Machine Learning, Head of AI, AI Lead, ML Lead, Principal ML Engineer, Machine Learning Manager, AI Research Lead, 3D Perception, Geometric Deep Learning, Computer Vision, GNN, Graph Neural Networks, 3D Transformers, NeRF, Point Clouds, CAD, Generative AI, Autonomous Agents, Robotics, PyTorch, MLOps, LLM, Reinforcement Learning, AI for Engineering, Simulation, Computational Geometry. Disclaimer Attis Global Ltd is an equal opportunities employer. No terminology in this advert is intended to discriminate on any of the grounds protected by law, and all qualified applicants will receive consideration for employment without regard to age, sex, race, national origin, religion or belief, disability, pregnancy and maternity, marital status, political affiliation, socio-economic status, sexual orientation, gender, gender identity and expression, and/or gender reassignment. M/F/D/V. We operate as a staffing agency and employment business. More information can be found at attisglobal.com.

Machine Learning Engineer - Applied AI Systems San Francisco, CA - On-site $170k-$250k + equity A venture-backed AI company is expanding its engineering group and looking for a Machine Learning Engineer to help push forward a new generation of decision-support products used in complex, data-heavy environments. The team builds systems that analyse large, unstructured datasets and surface insights that help organisations make high-stakes choices more consistently. You'll join a small group of engineers and researchers working on applied ML problems that combine pattern recognition, anomaly detection, language modelling and real-time data interpretation. This is a hands-on engineering role where you'll prototype, train, evaluate and productionise models that directly shape the product experience. What you'll work on Designing and implementing ML pipelines for processing a wide variety of semi-structured inputs. Training and adapting large language models to handle classification, extraction and reasoning tasks. Developing methods to identify irregularities, inconsistencies and unusual patterns within customer-supplied data. Improving the performance, latency and reliability of deployed models at scale. Collaborating with software engineers to integrate new capabilities into customer-facing features. Exploring new approaches in multimodal modelling, retrieval-augmented generation and adaptive learning systems. Who you might be Someone with professional experience in ML engineering, data science, applied research or similar. Confident programming in Python and fluent with at least one modern deep learning toolkit. Comfortable working with messy, real-world data rather than clean academic datasets. Experience with information extraction, language models, anomaly detection or data quality modelling is valuable. Interested in joining a company where the ML team has genuine influence over product direction. Enjoys experimentation, iteration and solving problems that don't have an obvious starting point. (No strict requirement on years - strength of experience matters more than time served.) Why this is different You'll work on technically challenging problems where accuracy genuinely matters. The company is scaling quickly and investing heavily in expanding its AI group. You'll collaborate closely with product and engineering leadership, not sit in a research silo. The environment is fast-moving, with opportunities to own projects end-to-end. Generous salary, equity and benefits package. Location & Work Style On-site in San Francisco to support a highly collaborative engineering culture. Hybrid flexibility may be available for senior hires already living in the Bay Area.

Staff AI Engineer | Sunnyvale, CA | $225K-$300K + Equity We're partnering with a leading company in the software defined vehicle space to hire a Staff AI Engineer. Their technology is already running in more than five million vehicles on the road today and they are now building the next layer of AI that will power future automotive platforms. In this role you will work on advanced language models, retrieval systems and agent style architectures that support real world, safety critical use cases. You will own the full lifecycle of AI systems from early research through to stable, production grade services. What you'll do: Train and fine tune LLMs for reasoning and decision making Build retrieval pipelines and RAG systems for real time semantic search Design and scale ML systems that run in fault tolerant, privacy compliant environments Develop evaluation frameworks to measure reliability, correctness and performance Work closely with engineering and product teams to shape AI solutions that match real world needs What we're looking for: 5+ years of experience as an AI or ML engineer Hands on experience with LLMs, agent frameworks and RAG architectures Strong Python and experience with PyTorch or TensorFlow Background in building and deploying production ML systems Comfort working in a collaborative on site environment three days per week in Sunnyvale If this sounds like something you would like to explore, apply today and we'll be in touch

Frontend Engineer Duration: 6+ months (possible extension) Type: W2 Contract (Open to Consider USC, GC, EAD) - No Third Party or C2C Experience: 6+ Years in an Enterprise Environment with BS or MS in Computer Science. Must Have: JavaScript, React.JS, Typescript, NodeJS and REST API Job Summary: Seeking a Frontend Engineer with strong experience in JavaScript, HTML, CSS, and hands-on expertise in React and Node.js. The role involves building scalable, high-quality UI components and collaborating in an Agile development environment. Responsibilities: Develop and maintain frontend modules using JavaScript, HTML, CSS, React, and Node.js. Implement unit testing (JUnit) and ensure code quality. Utilize jQuery and core data structures where applicable. Work closely with cross-functional teams in an Agile/Scrum setup. Participate in solution design, code reviews, and feature development. Required Skills: Bachelor's degree in Computer Science or related field with Strong proficiency in JavaScript, HTML, CSS. Must-have: React.js and Node.js. Experience with unit testing tools (JUnit). Good understanding of data structures and jQuery.

At Autonomous Healthcare, we are at the forefront of medical innovation, developing the next generation of devices that will revolutionize patient care. Our mission is to commercialize breakthrough medical technologies by leveraging cutting-edge AI and autonomous systems. We believe that the best solutions are built together, and we are looking for a key member to join our collaborative R&D team. About The Role Autonomous Healthcare is looking for a skilled Machine Learning Engineer to join our data science team. This role is focused on diving deep into complex datasets to uncover hidden patterns and build predictive models related to pharmacy data. You will be a key player in developing and deploying solutions that directly impact our business, with a special emphasis on analyzing unlabeled data to detect critical anomalies. If you love solving challenging puzzles with data and seeing your models come to life in a production environment, we want to hear from you. Key Responsibilities Design, develop, and train machine learning models to solve complex business problems. Perform in-depth data analysis and feature engineering on large, complex datasets, with a strong focus on unlabeled data to identify and investigate anomalies. Utilize Python and key libraries (such as Pandas, NumPy, and Scikit-learn) for data manipulation, analysis, and model building. Manage the end-to-end machine learning lifecycle, from data sourcing and model validation to deployment. Deploy and maintain scalable machine learning models in production on AWS (e.g., using SageMaker, Lambda, ECS/EKS). Collaborate with data engineers, software developers, and product managers to integrate ML models into our applications and systems. Monitor model performance, identify drift, and iterate on models to improve accuracy and efficiency. Required Qualifications Proven professional experience as a Machine Learning Engineer or Data Scientist. Strong programming skills in Python and extensive experience with data science/analytics libraries, especially Pandas. Demonstrable experience in analyzing unlabeled data and building models for anomaly detection (e.g., using clustering, isolation forests, autoencoders, or other techniques). Practical familiarity with deploying machine learning models on AWS cloud infrastructure (e.g., AWS SageMaker, S3, Lambda). Solid understanding of core machine learning concepts, algorithms, and best practices including unsupervised learning and reinforcement learning frameworks. Excellent analytical and problem-solving skills. Preferred Qualifications (A Plus) Familiarity with discrete event system simulation principles or tools. Experience with other MLOps tools and cloud services. A degree in Computer Science, Data Science, Statistics, or a related quantitative field.

About Us Mintegral is a leading programmatic and interactive mobile advertising platform, starting from the APAC region and radiating out globally. Powered by advanced AI technology, we provide global advertisers and developers with innovative, comprehensive experiences. With our efficient mobile marketing and monetization solutions, we help our clients exceed their marketing goals. As a self-developed programmatic platform, since Launched in 2015, Mintegral has quickly grown to become one of the largest mobile advertising platform in Asia. We offer a full stack of programmatic products and services including our Self-service Platform, DSP, SSP, Ad Exchange and DMP. We have also created the Mindworks Creative Studio, which offers publishers and brands cutting-edge creative solutions, from traditional creative right through to the latest interactive ad formats. For more information, please visit our website: ***************************** About the Role We are looking for a highly motivated Machine Learning Engineer to help advance the intelligence of our advertising platform. You will work across the full lifecycle of ML development-from framing ambiguous problems to deploying large-scale production models that directly impact advertiser ROI and user experience. Responsibilities Own the end-to-end algorithm development lifecycle, including problem formulation, solution design, experimental validation, and online deployment. Leverage data analysis and algorithmic innovation to optimize model inference performance, enhance monitoring systems, and continuously improve both monetization efficiency and user experience within the advertising platform. Identify potential issues and optimization opportunities across the ad delivery system. Actively participate in technical discussions, stay proactive in learning, and apply new technologies to solve real-world problems. Track cutting-edge research in machine learning and incorporate advanced techniques into practical adtech applications. Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, AI, Mathematics, Physics, or a closely related technical field; strong academic background preferred. Excellent problem-solving skills, with the ability to abstract complex problems, build models, and analyze large datasets. Strong engineering fundamentals and production-quality coding skills (Python, C++, or related languages). Self-driven, resilient, and able to navigate challenging problems with a proactive mindset. Hands-on experience with optimizing ad systems end-to-end, and understanding system behavior through data loops and feedback cycles. Practical experience with feature engineering, model architecture design, and sample distribution analysis; background in generative recommendation or LLM-based approaches is a plus. Experience in RTB and ads strategies, such as cold-start optimization, budget pacing, calibration, or bidding strategies, is strongly preferred.

Ascendion is a full-service digital engineering solutions company. We make and manage software platforms and products that power growth and deliver captivating experiences to consumers and employees. Our engineering, cloud, data, experience design, and talent solution capabilities accelerate transformation and impact for enterprise clients. Headquartered in New Jersey, our workforce of 6,000+ Ascenders delivers solutions from around the globe. Ascendion is built differently to engineer the next. Ascendion | Engineering to elevate life We have a culture built on opportunity, inclusion, and a spirit of partnership. Come, change the world with us: Build the coolest tech for world's leading brands Solve complex problems - and learn new skills Experience the power of transforming digital engineering for Fortune 500 clients Master your craft with leading training programs and hands-on experience Experience a community of change makers! Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion. *** About the Role *** Job Title: Machine Learning Engineer Key Responsibilities: Deploy and manage LLMs using TorchServe, TensorFlow Serving, or custom API endpoints. Optimize inference performance for large-scale GenAI workloads in real-time environments. Design and implement retrieval-based GenAI systems (e.g., RAG) using vector databases like FAISS, Pinecone, or Weaviate. Build, deploy, and scale ML services using Kubernetes and Docker for robust, fault-tolerant AI pipelines. Leverage Python and popular ML frameworks (PyTorch, TensorFlow) for fine-tuning, testing, and maintaining AI models. Utilize AWS SageMaker or similar cloud ML platforms for scalable training and deployment. Must-Have Skills: Proven experience in LLM deployment & optimization Strong understanding of GenAI architectures - particularly RAG and vector search Hands-on with Kubernetes, Docker, and container orchestration for ML workloads Experience with Python, PyTorch, TensorFlow Familiarity with vector databases: FAISS, Pinecone, Weaviate Exposure to cloud-based ML platforms like AWS SageMaker Salary Range: The salary for this position is between $130,000- $140,000 annually. Factors which may affect pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate. Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: [medical insurance] [dental insurance] [vision insurance] [401(k) retirement plan] [long-term disability insurance] [short-term disability insurance] [5 personal days accrued each calendar year. The Paid time off benefits meet the paid sick and safe time laws that pertains to the City/ State] [10-15 days of paid vacation time] [6 paid holidays and 1 floating holiday per calendar year] [Ascendion Learning Management System] Want to change the world? Let us know. Tell us about your experiences, education, and ambitions. Bring your knowledge, unique viewpoint, and creativity to the table. Let's talk!

It's fun to work in a company where people truly believe in what they're doing! At BlackLine, we're committed to bringing passion and customer focus to the business of enterprise applications. Since being founded in 2001, BlackLine has become a leading provider of cloud software that automates and controls the entire financial close process. Our vision is to modernize the finance and accounting function to enable greater operational effectiveness and agility, and we are committed to delivering innovative solutions and services to empower accounting and finance leaders around the world to achieve Modern Finance. Being a best-in-class SaaS Company, we understand that bringing in new ideas and innovative technology is mission critical. At BlackLine we are always working with new, cutting edge technology that encourages our teams to learn something new and expand their creativity and technical skillset that will accelerate their careers. Work, Play and Grow at BlackLine! The Principal AI/ML Operations Engineer leads the architecture, automation, and operationalization of both machine learning and AI systems at scale. This role defines the strategy and technical standards for ML-Ops and AIOps across the organization, ensuring models and agents are evaluated, deployed, governed, and monitored with reliability, efficiency, and compliance. The candidate will collaborate across AI, data, and product engineering teams to drive best practices for serving, observability, automated retraining, evaluation flywheels, and operational guardrails for AI systems in production You'll Get To: Leadership and Strategy Define enterprise-level standards and reference architectures for ML-Ops and AIOps systems. Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs). Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments. Lead incident response and reliability strategies for ML/AI systems. AI System Deployment and Integration: Lead the deployment of AI models and systems in various environments. Collaborate with development teams to integrate AI solutions into existing workflows and applications. Ensure seamless integration with different platforms and technologies. Define and manage MCP Registry for agentic component onboarding, lifecycle versioning, and dependency governance. Build CI/CD pipelines automating LLM agent deployment, policy validation, and prompt evaluation of workflows. Develop and operationalize experimentation frameworks for agent evaluations, scenario regression, and performance analytics. Implement logging, metering, and auditing for agent behavior, function calls, and compliance alignment. Create scalable observability systems-tracking conversation outcomes, factual accuracy, latency, escalation patterns, and safety events. Architect end-to-end guardrails for AI agents including prompt injection protection, identity-aware routing, and tool usage authorization. Collaborate cross-functionally to standardize authentication, authorization, and session governance for multi-agent runtimes. Model Deployment and Integration: Architect and standardize model registries and feature stores to support version tracking, lineage, and reproducibility across environments. Lead the deployment of machine learning models into production environments, ensuring scalability, reliability, and efficiency. Collaborate with software engineers to integrate machine learning models into existing applications and systems. Implement and maintain APIs for model inference. Infrastructure and Environment Management: Design and manage training infrastructure including distributed training orchestration, GPU/TPU resource allocation, and automatic scaling. Implement CI/CD for model workflows using pipelines integrated with model validation, bias checks, and rollback automation. Build standardized experimentation frameworks for reproducible training, tuning, and deployment cycles (MLflow, W&B, Kubeflow). Manage and optimize the infrastructure required for machine learning operations in cloud. Work closely with other teams to ensure the availability, security, and performance of machine learning systems. Monitoring and Maintenance: Implement robust monitoring solutions for deployed machine learning models to detect issues and ensure performance. Collaborate with data scientists and engineers to address and resolve model performance and data quality issues. Conduct regular system maintenance, updates, and optimizations to ensure optimal performance of machine learning solutions. Automation and Orchestration: Develop and maintain automation scripts and tools for managing machine learning workflows. Implement orchestration systems to streamline the end-to-end machine learning lifecycle, from data preparation to model deployment. Collaboration with Data Science Teams: Collaborate with data scientists to understand model requirements and constraints for deployment. Facilitate the transition of machine learning models from research to production, ensuring scalability and efficiency. Performance Optimization: Identify and implement optimizations to enhance the performance and efficiency of machine learning models in production. Conduct performance analysis and implement improvements based on resource utilization of metrics. Security and Compliance: Implement security measures to protect machine learning systems and data. Ensure compliance with regulatory requirements and industry standards related to machine learning and data privacy. Integrate audit controls, metadata storage, and lineage tracking across ML and AI workflows. Ensure complete monitoring and feedback loops including event logs, evaluations, and automated retraining triggers. Enforce secure deployment patterns with Infrastructure-as-Code and cloud-native secrets management. Define SLAs, error budgets, and compliance reporting mechanisms for ML and AI systems. What You'll Bring: Education and Experience: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. 10+ years in ML infrastructure, DevOps, and software system architecture; 4+ years in leading MLOps or AI Ops platforms. Technical Skills: Strong programming skills in languages such as Python, Java, or Scala. Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow). Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure). Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management. Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation. Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking. Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads. Proficiency in containerization technologies (e.g., Docker, Kubernetes). Operations and Infrastructure: Proficient in scripting languages (e.g., Bash, python) for automation. Experience with workflow orchestration tools (e.g., Apache Airflow). Expertise in managing and optimizing cloud-based infrastructure. Familiarity with DevOps practices and tools for automated deployment. Understanding of network configurations and security protocols. Problem-solving and Critical Thinking: Ability to define problems, collect and analyze data, and propose innovative solutions. Strong critical thinking skills to evaluate models, identify limitations, and Adaptability and Learning Agility: Comfortable working in a fast-paced, rapidly evolving environment. Proactive in staying up to date with the latest trends, techniques, and technologies in AI/data science Thrive at BlackLine Because You Are Joining: A technology-based company with a sense of adventure and a vision for the future. Every door at BlackLine is open. Just bring your brains, your problem-solving skills, and be part of a winning team at the world's most trusted name in Finance Automation! A culture that is kind, open, and accepting. It's a place where people can embrace what makes them unique, and the mix of cultural backgrounds and varying interests cultivates diverse thought and perspectives. A culture where BlackLiner's continued growth and learning is empowered. BlackLine offers a wide variety of professional development seminars and inclusive affinity groups to celebrate and support our diversity. BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws. BlackLine recognizes that the ways we work and the workplace itself have shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 2 days a week.

Project Engineer - Electrical (San Francisco, CA) A well-established Bay Area electrical contractor is seeking a Project Engineer to support major public-works projects across San Francisco. The company specializes in street-lighting systems, traffic signals, low-voltage infrastructure, ITS/communications, and overhead traction power systems for municipal transit. This role is ideal for an electrical engineer who wants to build a long-term career in electrical infrastructure and public utilities. Role Overview The Project Engineer will support project planning, coordination, documentation, and field execution. You'll work closely with Project Managers, Superintendents, and field crews to ensure successful delivery of complex municipal electrical projects. Key Responsibilities Project Coordination & Documentation Prepare RFIs, submittals, as-builts, change orders, and close-out packages Assist in developing schedules, phasing plans, and manpower forecasts Track quantities, production, materials, and delivery schedules Maintain communication with suppliers, subcontractors, and city inspectors Technical & Engineering Support Review and interpret plans, specifications, one-lines, and signal/lighting layouts Support engineering tasks for: Street-lighting and roadway illumination Traffic signals, pedestrian safety systems, and controllers Low-voltage ITS, communications, and fiber systems Overhead traction power used by electric bus fleets Assist with utility coordination, conduit routing, duct bank layout, and pole/fixture placement Participate in QA/QC checks and site inspections Field Support Conduct site walks and support daily project reporting Ensure work complies with NEC, Caltrans, and City & County of SF standards Assist with safety documentation and equipment tracking Cost Control & Estimating Support cost tracking, production reporting, and invoice review Assist with takeoffs and estimating for new bids and upcoming scopes Requirements Bachelor's degree in Electrical Engineering is required 0-5 years of experience in construction, electrical infrastructure, utilities, or low-voltage systems Strong understanding of electrical fundamentals (voltage, current flow, grounding, circuits) Ability to read plans, technical specifications, and electrical diagrams Strong organizational and communication skills Proficiency with MS Office; experience with Bluebeam, AutoCAD, or Procore is a plus Valid driver's license and willingness to perform site visits Compensation & Benefits Base salary: $80,000 - $120,000 DOE Company vehicle + fuel card 401(k) Health & dental insurance Paid time off and company-paid holidays Strong long-term career progression into Assistant Project Manager and Project Manager roles

We are seeking a motivated Senior Project Engineer in the San Francisco Bay Area to support the delivery of heavy civil and/or water infrastructure projects. The Senior Project Engineer works alongside the Project Management Team which is responsible to plan and oversee the project to ensure a timely and cost effective outcome. This includes budgeting, organization, implementation and scheduling of the project. Ensure the project is constructed in a safe, ethical manner and in compliance with all federal, state, and local laws. The Project Management Team can vary greatly depending on the size and complexity of the projects, which in turn will affect the number of responsibilities the Senior Project Engineer will be involved in. Responsibilities: Serve as a key member of the Project Management Team, supporting the planning and execution of projects. Assist with budgeting, organization, scheduling, and implementation throughout the project lifecycle. Ensure projects are delivered on time, within budget, and in alignment with quality expectations. Promote and maintain safe and ethical work practices. Ensure compliance with all applicable federal, state, and local regulations. Adapt responsibilities based on the size and complexity of each project. Qualifications: Bachelor's Degree - Construction or Engineering preferred or equivalent experience. 3+ years prior relevant experience. Requires deep knowledge of job area typically obtained through advanced education combined with experience. Benefits: Competitive Salary range (based on experience) Excellent Insurance Package 401k w/match and Company Benefits An amazing culture focused on Diversity and Inclusion

Mechanical Engineer (Robotics) We are partnering with a robotics company building complex electro-mechanical systems where mechanical design directly determines real-world performance. This role is for someone who doesn't just design parts, but owns motion, reliability, and scale. What You'll Do Own the end-to-end mechanical design of complex electro-mechanical systems with moving parts Design and prototype custom mechanisms and actuators under aggressive timelines Drive concepts from first prototype through high-volume production Personally design parts for volume manufacturing processes, including: Injection molding Die casting Stamping / sheet metal Extrusion Powder metal / MIM Partner closely with contract manufacturers (CMs) to ensure DFM, reliability, and cost targets are met Build systems that are not just elegant but robust, testable, and shippable at scale What We're Looking For Exceptionally strong mechanical intuition, you understand how things move, fail, and improve Proven ability to design and prototype quickly without sacrificing rigor Track record of shipping reliable, hardware products at scale Deep hands-on experience designing custom mechanisms, joints, transmissions, and actuators Experience owning mechanical architecture for complex systems with dynamic loads and tight tolerances Comfortable operating across ambiguity, tight timelines, and high expectations Required Background Currently working at a robotics company (hands-on mechanical role) Background in electro-mechanical systems with real moving parts (not CAD-only work) Experience taking designs from concept → prototype → volume production Ideal Signals Designed robotic arms, legs, mobile platforms, end-effectors, or actuation systems Personally responsible for motor selection, gearing, kinematics, or load paths Close collaboration with electrical and controls teams Bias for execution and ownership over documentation and theory

Lead Machine Learning Engineer - Generative AI for the Physical World A rare opportunity has emerged for a visionary Lead Machine Learning Engineer to build the core intelligence for a stealth-mode, well-funded AI company. This foundational leadership role is for someone passionate about teaching machines to understand and engineer the physical world, moving beyond language and into the complex domain of 3D geometry and physics. Why Join? This is a chance to define a new category of software from the ground up. You will have the autonomy to set the technical vision, build a world-class team, and solve fundamental AI challenges that directly impact how next-generation products are designed and built. You will be instrumental in creating the "brain" that powers a revolutionary platform. The Company My client is a pioneering startup developing a new class of generative AI. Their platform uses autonomous agents to design, test, and optimize complex physical systems, aiming to radically accelerate today's slow and manual engineering cycles. Backed by top-tier investors, the company is positioned to become a leader in the application of AI to advanced hardware design and manufacturing. The Role As the Lead Machine Learning Engineer, you will architect the company's entire ML strategy. You will lead the research and development of the core models that allow AI agents to perceive and reason about 3D geometry. Your primary focus will be on defining the technical roadmap, hiring and mentoring a high-performing team, and guiding the development of novel techniques in geometric deep learning and multimodal reasoning. The Essential Requirements Proven experience leading machine learning teams, setting technical direction, and mentoring senior engineers. Deep expertise in 3D perception, scene understanding, or geometric deep learning (e.g., from robotics, AV, AR/VR). A strong track record of architecting and deploying complex ML systems from research to production. Fluency with modern ML frameworks (e.g., PyTorch) and models for geometric data (GNNs, 3D CNNs, NeRFs). Ability to translate ambiguous product goals into a concrete technical roadmap and execute effectively. What Will Make You Stand Out A PhD in a relevant field such as Computer Science or Robotics. A background in mechanical, aerospace, or a related engineering discipline. Experience integrating perception models with LLMs or other agent-based systems. A history of publications in top-tier machine learning conferences. Benefits Up to $260,000 base Meaningful equity A key leadership role with the autonomy to shape the company's technical culture and direction. The opportunity to solve high-impact problems at the intersection of AI and engineering. If you are interested in this role, please apply with your resume through this site. SEO Keywords for Search Head of Machine Learning, Head of AI, AI Lead, ML Lead, Principal ML Engineer, Machine Learning Manager, AI Research Lead, 3D Perception, Geometric Deep Learning, Computer Vision, GNN, Graph Neural Networks, 3D Transformers, NeRF, Point Clouds, CAD, Generative AI, Autonomous Agents, Robotics, PyTorch, MLOps, LLM, Reinforcement Learning, AI for Engineering, Simulation, Computational Geometry. Disclaimer Attis Global Ltd is an equal opportunities employer. No terminology in this advert is intended to discriminate on any of the grounds protected by law, and all qualified applicants will receive consideration for employment without regard to age, sex, race, national origin, religion or belief, disability, pregnancy and maternity, marital status, political affiliation, socio-economic status, sexual orientation, gender, gender identity and expression, and/or gender reassignment. M/F/D/V. We operate as a staffing agency and employment business. More information can be found at attisglobal.com.

Machine Learning Engineer - Applied AI Systems San Francisco, CA - On-site $170k-$250k + equity A venture-backed AI company is expanding its engineering group and looking for a Machine Learning Engineer to help push forward a new generation of decision-support products used in complex, data-heavy environments. The team builds systems that analyse large, unstructured datasets and surface insights that help organisations make high-stakes choices more consistently. You'll join a small group of engineers and researchers working on applied ML problems that combine pattern recognition, anomaly detection, language modelling and real-time data interpretation. This is a hands-on engineering role where you'll prototype, train, evaluate and productionise models that directly shape the product experience. What you'll work on Designing and implementing ML pipelines for processing a wide variety of semi-structured inputs. Training and adapting large language models to handle classification, extraction and reasoning tasks. Developing methods to identify irregularities, inconsistencies and unusual patterns within customer-supplied data. Improving the performance, latency and reliability of deployed models at scale. Collaborating with software engineers to integrate new capabilities into customer-facing features. Exploring new approaches in multimodal modelling, retrieval-augmented generation and adaptive learning systems. Who you might be Someone with professional experience in ML engineering, data science, applied research or similar. Confident programming in Python and fluent with at least one modern deep learning toolkit. Comfortable working with messy, real-world data rather than clean academic datasets. Experience with information extraction, language models, anomaly detection or data quality modelling is valuable. Interested in joining a company where the ML team has genuine influence over product direction. Enjoys experimentation, iteration and solving problems that don't have an obvious starting point. (No strict requirement on years - strength of experience matters more than time served.) Why this is different You'll work on technically challenging problems where accuracy genuinely matters. The company is scaling quickly and investing heavily in expanding its AI group. You'll collaborate closely with product and engineering leadership, not sit in a research silo. The environment is fast-moving, with opportunities to own projects end-to-end. Generous salary, equity and benefits package. Location & Work Style On-site in San Francisco to support a highly collaborative engineering culture. Hybrid flexibility may be available for senior hires already living in the Bay Area.

Job Title: Electrical Design Engineer 4 Work Schedule: On-site Rate: $71, Based on experience. Responsibilities: Designs electrical parts, modules and subsystems to support the design of whole systems. Responsible for the complete design process, including requirements specification, feasibility studies, cost and scheduling, conducting various hand-on testing and analysis, such as circuit, timing, thermal/cooling, electrical loads; conceptual and detailed design using design tools (i.e. OrCAD, PSpice, etc...), detailed drawings, design review presentations, procurement of prototype parts, system integration, prototype testing, and handoff to manufacturing. These tasks will require working with other engineering groups such as ME, OE, SW, systems and manufacturing engineers to ensure flawless integration and test at the subsystem and system level. Develops the required supporting documentation, such as assembly and test procedures, and service manuals. Works closely with and manages suppliers to ensure all design requirements are specified and achieved. Addresses and resolves product issues thru the product phases. Has strong leadership, communication and problem solving skills. Minimum B.S. in electrical engineering 5 years experience Skills: Category Name Required Importance Experience Area of Expertise Electromechanical No 2 Area of Expertise Schematic Capture No 1 Areas of Expertise Circuit Design No 1 Areas of Expertise Electrical Troubleshooting No 1 Technical Skills Circuit Failure Mode Analysis No 1 Technical Skills Electrical Testing No 1 Technical Skills Schematic Development No 1 About Maxonic: Since 2002 Maxonic has been at the forefront of connecting candidate strengths to client challenges. Our award winning, dedicated team of recruiting professionals are specialized by technology, are great listeners, and will seek to find a position that meets the long-term career needs of our candidates. We take pride in the over 10,000 candidates that we have placed, and the repeat business that we earn from our satisfied clients. Interested in Applying? Please apply with your most current resume. Feel free to contact Lavanya Dommeti (********************* / *************** for more details.