Data scientist jobs in Hayward, CA

We're working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics. We're seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability. This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions. Key Responsibilities Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records) Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers Research and prototype innovative approaches leveraging both classical and modern machine learning techniques Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments Collaborate cross-functionally with data engineers, clinicians, and product teams to ensure models address real-world healthcare needs Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations Required Qualifications Strong foundation in statistical modeling, machine learning, or data science, with preference for experience in temporal or longitudinal data analysis Proficiency in Python and ML frameworks (PyTorch, JAX, NumPyro, PyMC, etc.) Proven track record of transitioning models from research prototypes to production systems Experience with probabilistic methods, survival analysis, or Bayesian inference (highly valued) Bonus Qualifications Experience working with clinical data and healthcare terminologies (ICD, CPT, SNOMED CT, LOINC) Background in actuarial modeling, claims forecasting, or risk adjustment methodologies

Lead Data Scientist - Computer Vision/Image Processing About the Role We are seeking a Lead Data Scientist to drive the strategy and execution of data science initiatives, with a particular focus on computer vision systems & image processing techniques. The ideal candidate has deep expertise in image processing techniques including Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection. Responsibilities Solid knowledge of computer vision programs and image processing techniques: Filtering, Binary Morphology, Perspective/Affine Transformation, Edge Detection Strong understanding of machine learning: Regression, Supervised and Unsupervised Learning Proficiency in Python and libraries such as OpenCV, NumPy, scikit-learn, TensorFlow/PyTorch. Familiarity with version control (Git) and collaborative development practices

Onsite in Cupertino, CA from Day 1 (Client prefer local folks) Hybrid Schedule: 3 Onsite Days (Tue, Wed, Thur) & 2 Remote Days (Mon, Fri) Long term contract Direct client opportunity No Mid layer / No Implementation partners are Involved Key points - Need someone focused on product management and integration of generative AI solutions - Excellent communication, organizational, and problem-solving skills We are seeking an AI Engineer to join our Legal Operations team and lead the design, development and deployment of AI-powered tools and automation solutions that transform how our Legal Department operates. This is a unique opportunity for a technically skilled and product-minded professional who can bridge the gap between engineering, legal, and business functions. You will work closely with attorneys, legal ops specialists, and other engineering teams to identify opportunities for AI-driven efficiency, develop prototypes and bring scalable solutions to life. The ideal candidate combines strong software engineering and AI expertise with excellent communication skills, product sensibility and a curiosity about legal workflows and technology Description As a Senior Data Scientist/ AI Engineer, you will be responsible for overseeing the design and execution of key tool development programs. This is a unique opportunity for a technically skilled and product-minded professional who can bridge the gap between engineering, legal, and business functions. You will work closely with attorneys, legal ops specialists, and other engineering teams to identify opportunities for AI-driven efficiency, develop prototypes and bring scalable solutions to life. The ideal candidate combines strong software engineering and AI expertise with excellent communication skills, product sensibility and a curiosity about legal workflows and technology. Key responsibilities may include: Develop and deploy AI solutions that enhance legal workflows, including contract review, document classification, knowledge management and workflow automation. Collaborate cross-functionally with attorneys, legal operations, compliance and engineering teams to identify and prioritize AI use cases. Act as a product developer and owner from concept to rollout-defining requirements, developing proofs of concept, collecting feedback and iterating solutions. Integrate large language models (LLMs) and other AI technologies into existing systems (e.g., document management, eDiscovery, CLM, or knowledge bases). Evaluate and integrate third-party legal AI tools and platforms as needed, ensuring compatibility and compliance with internal systems. Maintain strong documentation and governance around data usage, model performance and ethical AI standards. Stay current on emerging trends in AI, machine learning and legal tech to help shape the department's AI strategy. Minimum Qualifications Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience). 5+ years of experience building and deploying AI/ML or automation solutions in production environments. Strong programming skills in Python (proven ability to quickly master new frameworks and tools). Demonstrated experience with modern AI architectures including context engineering, tool use and retrieval augmented generation. Proven ability to communicate complex technical concepts to non-technical stakeholders. Strong product development mindset-able to translate business needs into practical, scalable AI tools. Prior experience in or exposure to legal tech or legal operations. Preferred Qualifications Familiarity with DMS, document intelligence and CLM systems (e.g., Ironclad, Icertis, DocuSign CLM), document management platforms (e.g., iManage, NetDocuments) or legal AI tools (e.g., Harvey, Luminance, Casetext, Spellbook, etc.). Experience building internal AI assistants or chatbots for enterprise knowledge retrieval. Understanding of data privacy, compliance and governance frameworks relevant to legal data. Pay Range: $65/hr - $70/hr The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision as well as 401K contributions.

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow's ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries. ******NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future*** Summary: The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Job Responsibilities: • Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. • Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. • Generate and test hypotheses and analyze and interpret the results of product experiments. • Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation. • Provide Business Intelligence (BI) and data visualization support, which includes, but limited to support for the online customer service dashboards and other ad-hoc requests requiring data analysis and visual support. Skills: • Experienced in either programming languages such as Python and/or R, big data tools such as Hadoop, or data visualization tools such as Tableau. • The ability to communicate effectively in writing, including conveying complex information and promoting in-depth engagement on course topics. • Experience working with large datasets. Education/Experience: • Master of Science degree in computer science or in a relevant field.

Member of Technical Staff - AI Data Engineer San Francisco (In-Office) $150K to $225K + Equity A high-growth, AI-native startup coming out of stealth is hiring AI Data Engineers to build the systems that power production-grade AI. The company has recently signed a Series A term sheet and is scaling rapidly. This role is central to unblocking current bottlenecks across data engineering, context modeling, and agent performance. Responsibilities: • Build distributed, reliable data pipelines using Airflow, Temporal, and n8n • Model SQL, vector, and NoSQL databases (Postgres, Qdrant, etc.) • Build API and function-based services in Python • Develop custom automations (Playwright, Stagehand, Zapier) • Work with AI researchers to define and expose context as services • Identify gaps in data quality and drive changes to upstream processes • Ship fast, iterate, and own outcomes end-to-end Required Experience: • Strong background in data engineering • Hands-on experience working with LLMs or LLM-powered applications • Data modeling skills across SQL and vector databases • Experience building distributed systems • Experience with Airflow, Temporal, n8n, or similar workflow engines • Python experience (API/services) • Startup mindset and bias toward rapid execution Nice To Have: • Experience with stream processing (Flink) • dbt or Clickhouse experience • CDC pipelines • Experience with context construction, RAG, or agent workflows • Analytical tooling (Posthog) What You Can Expect: • High-intensity, in-office environment • Fast decision-making and rapid shipping cycles • Real ownership over architecture and outcomes • Opportunity to work on AI systems operating at meaningful scale • Competitive compensation package • Meals provided plus full medical, dental, and vision benefits If this sounds like you, please apply now.

Net2Source is a Global Workforce Solutions Company headquartered at NJ, USA with its branch offices in Asia Pacific Region. We are one of the fastest growing IT Consulting company across the USA and we are hiring " Bigdata Engineer " for one of our clients. We offer a wide gamut of consulting solutions customized to our 450+ clients ranging from Fortune 500/1000 to Start-ups across various verticals like Technology, Financial Services, Healthcare, Life Sciences, Oil & Gas, Energy, Retail, Telecom, Utilities, Technology, Manufacturing, the Internet, and Engineering. Position: Bigdata Engineer Location: MTV, CA (Onsite) - Locals Only Type: Contract Exp Level - 10+ Years Required Skills Min of 7+ years working with Apache Flink and Apache Spark 5+ years' experience with Java Strong expertise in Python Expertise developing new pipelines Adept at supporting and enhancing existing pipelines Strong experience with AWS Stack Why Work With Us? We believe in more than just jobs-we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter. Our Commitment to Inclusion & Equity Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics. Awards & Recognition America's Most Honored Businesses (Top 10%) Fastest-Growing Staffing Firm by Staffing Industry Analysts INC 5000 List for Eight Consecutive Years Top 100 by Dallas Business Journal Spirit of Alliance Award by Agile1 Maddhuker Singh Sr Account & Delivery Manager ***********************

You'll work closely with engineering, analytics, and product teams to ensure data is accurate, accessible, and efficiently processed across the organization. Key Responsibilities: Design, develop, and maintain scalable data pipelines and architectures. Collect, process, and transform data from multiple sources into structured, usable formats. Ensure data quality, reliability, and security across all systems. Work with data analysts and data scientists to optimize data models for analytics and machine learning. Implement ETL (Extract, Transform, Load) processes and automate workflows. Monitor and troubleshoot data infrastructure, ensuring minimal downtime and high performance. Collaborate with cross-functional teams to define data requirements and integrate new data sources. Maintain comprehensive documentation for data systems and processes. Requirements: Proven experience as a Data Engineer, ETL Developer, or similar role. Strong programming skills in Python, SQL, or Scala. Experience with data pipeline tools (Airflow, dbt, Luigi, etc.). Familiarity with big data technologies (Spark, Hadoop, Kafka, etc.). Hands-on experience with cloud data platforms (AWS, GCP, Azure, Snowflake, or Databricks). Understanding of data modeling, warehousing, and schema design. Solid knowledge of database systems (PostgreSQL, MySQL, NoSQL). Strong analytical and problem-solving skills.

We're looking for a Lead Data Engineer to spearhead the design, implementation, and iteration of a world-class, modern data infrastructure that powers analytics, data science, and ML/AI systems. You will be in the driver's seat for a new function on the Engineering team and will help chart its future. This role is highly strategic, cross-functional, and hands-on. If you're passionate about building 0→1 data platforms collaboratively and have experience scaling them at a rapidly growing startup, this role is for you. What you will do Define and execute the strategic roadmap for data infrastructure and analytics capabilities across the organization. Partner closely with Data Science, Operations Analytics, Engineering, and Product on the design and implementation of scalable data pipelines, models, and solutions. Drive the development of foundational data products and tools to power self-service analytics. Actively contribute to and influence engineering processes, culture, practices, and systems. Serve as a technical thought leader on data engineering best practices. About you Strong technical foundation with the modern data engineering stack (dbt, PySpark, Fivetran, Snowflake, Lakehouse, CDPs, ETL tools, etc.). Advanced knowledge of SQL and Python. Deep expertise in data pipelines, distributed systems, and analytics infrastructure. Hands-on experience with data warehousing technologies, data lake architecture, and ETL pipelines/tools. Deep understanding of BI tooling infrastructure and semantic layer design (e.g., Looker, Tableau, Metabase, Mode). Experience and interest in leading major architecture initiatives from the ground up. Believer in applying best-in-class software engineering practices to data systems. Interest in coaching/mentoring junior engineers. Bonus points Experience building data products that meet HIPAA requirements. Built platforms that support real-time and batch ML/AI products and systems. Experience integrating EHR and other complex third-party system data. For more info or to apply please share your resume to *************************.

Midjourney is a research lab exploring new mediums to expand the imaginative powers of the human species. We are a small, self-funded team focused on design, human infrastructure, and AI. We have no investors, no big company controlling us, and no advertisers. We are 100% supported by our amazing community. Our tools are already used by millions of people to dream, to explore, and to create. But this is just the start. We think the story of the 2020s is about building the tools that will remake the world for the next century. We're making those tools, to expand what it means to be human. Core Responsibilities: Design and maintain data pipelines to consolidate information across multiple sources (subscription platforms, payment systems, infrastructure and usage monitoring, and financial systems) into a unified analytics environment Build and manage interactive dashboards and self-service BI tools that enable leadership to track key business metrics including revenue performance, infrastructure costs, customer retention, and operational efficiency Serve as technical owner of our financial planning platform (Pigment or similar), leading implementation and build-out of models, data connections, and workflows in partnership with Finance leadership to translate business requirements into functional system architecture Develop automated data quality checks and cleaning processes to ensure accuracy and consistency across financial and operational datasets Partner with Finance, Product and Operations teams to translate business questions into analytical frameworks, including cohort analysis, cost modeling, and performance trending Create and maintain documentation for data models, ETL processes, dashboard logic, and system workflows to ensure knowledge continuity Support strategic planning initiatives by building financial models, scenario analyses, and data-driven recommendations for resource allocation and growth investments Required Qualifications: 3-5+ years experience in data engineering, analytics engineering, or similar role with demonstrated ability to work with large-scale datasets Strong SQL skills and experience with modern data warehousing solutions (BigQuery, Snowflake, Redshift, etc.) Proficiency in at least one programming language (Python, R) for data manipulation and analysis Experience with BI/visualization tools (Looker, Tableau, Power BI, or similar) Hands-on experience administering enterprise financial systems (NetSuite, SAP, Oracle, or similar ERP platforms) Experience working with Stripe Billing or similar subscription management platforms, including data extraction and revenue reporting Ability to communicate technical concepts clearly to non-technical stakeholders

If you're hands on with modern data platforms, cloud tech, and big data tools and you like building solutions that are secure, repeatable, and fast, this role is for you. As a Senior Data Engineer, you will design, build, and maintain scalable data pipelines that transform raw information into actionable insights. The ideal candidate will have strong experience across modern data platforms, cloud environments, and big data technologies, with a focus on building secure, repeatable, and high-performing solutions. Responsibilities: Design, develop, and maintain secure, scalable data pipelines to ingest, transform, and deliver curated data into the Common Data Platform (CDP). Participate in Agile rituals and contribute to delivery within the Scaled Agile Framework (SAFe). Ensure quality and reliability of data products through automation, monitoring, and proactive issue resolution. Deploy alerting and auto-remediation for pipelines and data stores to maximize system availability. Apply a security first and automation-driven approach to all data engineering practices. Collaborate with cross-functional teams (data scientists, analysts, product managers, and business stakeholders) to align infrastructure with evolving data needs. Stay current on industry trends and emerging tools, recommending improvements to strengthen efficiency and scalability. Qualifications: Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent experience). At least 3 years of experience with Python and PySpark, including Jupyter notebooks and unit testing. At least 2 years of experience with Databricks, Collibra, and Starburst. Proven work with relational and NoSQL databases, including STAR and dimensional modeling approaches. Hands-on experience with modern data stacks: object stores (S3), Spark, Airflow, lakehouse architectures, and cloud warehouses (Snowflake, Redshift). Strong background in ETL and big data engineering (on-prem and cloud). Work within enterprise cloud platforms (CFS2, Cloud Foundational Services 2/EDS) for governance and compliance. Experience building end-to-end pipelines for structured, semi-structured, and unstructured data using Spark.

Zigma LLC is a women-owned technology consulting and IT services start-up specializing in Big Data engineering, cloud data modernization, cloud architecture, and advanced analytics. Our mission is to empower organizations through secure, scalable, and high-performance digital ecosystems while maintaining a strong commitment to cybersecurity and compliance. We work with clients across various industries, including healthcare, telecom, and financial services, ranging from local businesses to enterprise-level corporations. Dedicated to fostering inclusion and women's leadership, we strive to deliver innovative solutions that drive operational efficiency and digital transformation. Zigma LLC combines technical expertise with a passion for empowering the next generation of women entrepreneurs. Data Engineer (Mid-Level) - Hybrid | C2C | Healthcare Locations: East Bay Area, CA | Greater Los Angeles Area, CA | Oregon's Willamette Valley, OR | Greater Atlanta Area, GA Employment Type: C2C Work Authorization: US Citizens, Green Card, H4/L2/Any EAD, OPT/CPT Candidates. Work Arrangement: Hybrid Openings: 3 per location Experience: 7-12 years Contract: Long-term (12+ months, performance-based) Preferred Education/Certification: B.S/M.S. in Engineering Discipline with Computer Science, Data Engineering or relevant skills and certifications Join a leading healthcare analytics team as a Data Engineer! Work on Azure Cloud, Databricks, and modern Data Pipelines to drive insights from complex healthcare datasets. This is a hybrid role with opportunities to collaborate across multiple locations. Key Responsibilities: • Design, build, and maintain ETL/ELT Ingestion pipelines on Azure Cloud • Collaborate with data scientists and analysts to ensure data quality, governance, and availability • Implement batch and streaming data processing workflows • Optimize data workflows and pipelines for performance and scalability • Work with HIPAA-compliant healthcare data Technical Skills & Tools: Programming & Scripting: Python, SQL, Scala/Java Data Processing Frameworks: Apache Spark, Kafka, Airflow/Prefect Databases: Relational (PostgreSQL, MySQL, SQL Server), NoSQL (MongoDB, Cassandra), Data Warehouses (Snowflake, Redshift) Data Formats: CSV, JSON, Parquet, Avro, ORC Version Control & DevOps: Git, Azure DevOps, CI/CD pipelines Cloud & Containerization: Azure Cloud, Docker, Kubernetes, Terraform Core Skills: • ETL/ELT Ingestion pipeline design • Batch & streaming data processing • Data modelling (star/snowflake schema) • Performance optimization & scalability • Data governance and security Must-Have: • 7-12 years in Data Engineering • Hands-on Azure Cloud and Databricks experience • M.S. in Data Science or relevant certifications (Databricks/Data Science)

We are actively searching for a Data Infrastructure Engineer to join our team on a permanent basis. In this founding engineer role you will focus on building next-generation data infrastructure for our AI platform. If you have a passion for distributed systems, unified storage, orchestration, and retrieval for AI workloads we would love to speak with you. Your Rhythm: Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient Tackle complex challenges in distributed systems, databases, and AI infrastructure Collaborate with technical leadership to define and refine the product roadmap Write high-quality, well-tested, and maintainable code Contribute to the open-source community and engage with developers in the space Your Vibe: 5+ years experience designing building distributed database systems Expertise in building and operating scalable, reliable and secure database infrastructure systems Strong knowledge around distributed compute, data orchestration, distributed storage, streaming infrastructure Strong knowledge of SQL and NoSQL databases, such as MySQL, Postgres, and MongoDB. Programming skills in Python Passion for building developer tools and scalable infrastructure Our Vibe: Relaxed work environment 100% paid top of the line health care benefits Full ownership, no micro management Strong equity package 401K Unlimited vacation An actual work/life balance, we aren't trying to run you into the ground. We have families and enjoy life too!

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.

Member of Technical Staff - AI Data Engineer San Francisco (In-Office) $150K to $225K + Equity A high-growth, AI-native startup coming out of stealth is hiring AI Data Engineers to build the systems that power production-grade AI. The company has recently signed a Series A term sheet and is scaling rapidly. This role is central to unblocking current bottlenecks across data engineering, context modeling, and agent performance. Responsibilities: • Build distributed, reliable data pipelines using Airflow, Temporal, and n8n • Model SQL, vector, and NoSQL databases (Postgres, Qdrant, etc.) • Build API and function-based services in Python • Develop custom automations (Playwright, Stagehand, Zapier) • Work with AI researchers to define and expose context as services • Identify gaps in data quality and drive changes to upstream processes • Ship fast, iterate, and own outcomes end-to-end Required Experience: • Strong background in data engineering • Hands-on experience working with LLMs or LLM-powered applications • Data modeling skills across SQL and vector databases • Experience building distributed systems • Experience with Airflow, Temporal, n8n, or similar workflow engines • Python experience (API/services) • Startup mindset and bias toward rapid execution Nice To Have: • Experience with stream processing (Flink) • dbt or Clickhouse experience • CDC pipelines • Experience with context construction, RAG, or agent workflows • Analytical tooling (Posthog) What You Can Expect: • High-intensity, in-office environment • Fast decision-making and rapid shipping cycles • Real ownership over architecture and outcomes • Opportunity to work on AI systems operating at meaningful scale • Competitive compensation package • Meals provided plus full medical, dental, and vision benefits If this sounds like you, please apply now.

This will be a data engineer role for processing battery testing data to facilitate battery algorithm delivery and support battery algorithm simulations to validate the battery algorithm and project the product KPIs. Requires battery modeling and algorithm knowledge and hands on experiences in data analysis and Matlab programing. Experience with Matlab is required, C++/python is a plus Experience with machine learning, optimization, and control algorithms is a plus Degree in DataScience/EE/CS/ChemE/MechE is preferred. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit ***************** At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $75 - $85 The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at ***************. To report any concerns, please email us at *******************

We're the data team behind Midjourney's image generation models. We handle the dataset side: processing, filtering, scoring, captioning, and all the distributed compute that makes high-quality training data possible. What you'd be working on: Large-scale dataset processing and filtering pipelines Training classifiers for content moderation and quality assessment Models for data quality and aesthetic evaluation Data visualization tools for experimenting on dataset samples Testing/simulating distributed inference pipelines Monitoring dashboards for data quality and pipeline health Performance optimization and infrastructure scaling Occasionally jumping into inference optimization and other cross-team projects Our current stack: PySpark, Slurm, distributed batch processing across hybrid cloud setup. We're pragmatic about tools - if there's something better, we'll switch. We're looking for someone strong in either: Data engineering/ML pipelines at scale, or Cloud/infrastructure with distributed systems experience Don't need exact tech matches - comfort with adjacent technologies and willingness to learn matters more. We work with our own hardware plus GCP and other providers, so adaptability across different environments is valuable. Location: SF office a few times per week (we may make exceptions on location for truly exceptional candidates) The role offers variety, our team members often get pulled into different projects across the company, from dataset work to inference optimization. If you're interested in the intersection of large-scale data processing and cutting-edge generative AI, we'd love to hear from you.

If you're hands on with modern data platforms, cloud tech, and big data tools and you like building solutions that are secure, repeatable, and fast, this role is for you. As a Senior Data Engineer, you will design, build, and maintain scalable data pipelines that transform raw information into actionable insights. The ideal candidate will have strong experience across modern data platforms, cloud environments, and big data technologies, with a focus on building secure, repeatable, and high-performing solutions. Responsibilities: Design, develop, and maintain secure, scalable data pipelines to ingest, transform, and deliver curated data into the Common Data Platform (CDP). Participate in Agile rituals and contribute to delivery within the Scaled Agile Framework (SAFe). Ensure quality and reliability of data products through automation, monitoring, and proactive issue resolution. Deploy alerting and auto-remediation for pipelines and data stores to maximize system availability. Apply a security first and automation-driven approach to all data engineering practices. Collaborate with cross-functional teams (data scientists, analysts, product managers, and business stakeholders) to align infrastructure with evolving data needs. Stay current on industry trends and emerging tools, recommending improvements to strengthen efficiency and scalability. Qualifications: Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent experience). At least 3 years of experience with Python and PySpark, including Jupyter notebooks and unit testing. At least 2 years of experience with Databricks, Collibra, and Starburst. Proven work with relational and NoSQL databases, including STAR and dimensional modeling approaches. Hands-on experience with modern data stacks: object stores (S3), Spark, Airflow, lakehouse architectures, and cloud warehouses (Snowflake, Redshift). Strong background in ETL and big data engineering (on-prem and cloud). Work within enterprise cloud platforms (CFS2, Cloud Foundational Services 2/EDS) for governance and compliance. Experience building end-to-end pipelines for structured, semi-structured, and unstructured data using Spark.

We are actively searching for a Data Infrastructure Engineer to join our team on a permanent basis. In this founding engineer role you will focus on building next-generation data infrastructure for our AI platform. If you have a passion for distributed systems, unified storage, orchestration, and retrieval for AI workloads we would love to speak with you. Your Rhythm: Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient Tackle complex challenges in distributed systems, databases, and AI infrastructure Collaborate with technical leadership to define and refine the product roadmap Write high-quality, well-tested, and maintainable code Contribute to the open-source community and engage with developers in the space Your Vibe: 5+ years experience designing building distributed database systems Expertise in building and operating scalable, reliable and secure database infrastructure systems Strong knowledge around distributed compute, data orchestration, distributed storage, streaming infrastructure Strong knowledge of SQL and NoSQL databases, such as MySQL, Postgres, and MongoDB. Programming skills in Python Passion for building developer tools and scalable infrastructure Our Vibe: Relaxed work environment 100% paid top of the line health care benefits Full ownership, no micro management Strong equity package 401K Unlimited vacation An actual work/life balance, we aren't trying to run you into the ground. We have families and enjoy life too!

Staff Data Scientist | San Francisco | $250K-$300K + Equity We're partnering with one of the fastest-growing AI companies in the world to hire a Staff Data Scientist. Backed by over $230M from top-tier investors and already valued at over $1B, they've secured customers that include some of the most recognizable names in tech. Their AI platform powers millions of daily interactions and is quickly becoming the enterprise standard for conversational AI. In this role, you'll bring rigorous analytics and experimentation leadership that directly shapes product strategy and company performance. What you'll do: Drive deep-dive analyses on user behavior, product performance, and growth drivers Design and interpret A/B tests to measure product impact at scale Build scalable data models, pipelines, and dashboards for company-wide use Partner with Product and Engineering to embed experimentation best practices Evaluate ML models, ensuring business relevance, performance, and trade-off clarity What we're looking for: 5+ years in data science or product analytics at scale (consumer or marketplace preferred) Advanced SQL and Python skills, with strong foundations in statistics and experimental design Proven record of designing, running, and analyzing large-scale experiments Ability to analyze and reason about ML models (classification, recommendation, LLMs) Strong communicator with a track record of influencing cross-functional teams If you're excited by the sound of this challenge- apply today and we'll be in touch.