Machine Learning Scientist Jobs in San Francisco, CA
Machine Learning Scientist jobs in San Francisco concentrate in SoMa, Mission Bay, and the Financial District, with strong demand from AI research labs, enterprise software companies, and biotech firms. Employers actively hiring include Lila Sciences, Genentech, and Merge Labs. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 89+ Machine Learning Scientist jobs
Data Science - San Francisco
About the Team
The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.
We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential.
About the Role
We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability.
This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains.
Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability.
Contribute to self-service forecasting tools and internal platforms, enabling teams across OpenAI to access and act on real-time predictions.
Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches.
Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks.
Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making.
You might thrive in this role if you have:
Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability.
Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0 1.
Bonus if you have:
Experience building or scaling forecasting platforms in a high-growth company.
Familiarity with causal inference, Bayesian forecasting.
Experience building agentic decision support systems.
Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core the full spectrum of humanity.
We are an equal opportunity employeration, or other applicable legally protected characteristic.
Background checks for applicants will be administered in accordance with applicable lawation technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities.
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Compensation
$347K – $445K + Offers Equity
The base pay offered may vary depending on multiple individualized factorsance-related bonus(es) for eligible employees, and the following benefits.
Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible
Relocation support for eligible employees
Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
More details about our benefits are available to candidates during the hiring process.
This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
Data Science - San Francisco
About the Team
The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.
We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential.
About the Role
We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability.
This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains.
Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
Develop and productionize scalable, interpretable forecasts for user growth, monetization, compute load, customer lifetime value, and profitability.
Contribute to self-service forecasting tools and internal platforms, enabling teams across OpenAI to access and act on real-time predictions.
Research and evaluate emerging tools and techniques in the forecasting space, such as TimeGPT, large language model extensions, causal forecasting, and hybrid approaches.
Drive strategic insight generation by translating technical outputs into business-aligned recommendations and decision frameworks.
Collaborate closely with cross-functional teams to ensure forecasts are well-integrated into planning processes, experimentation workflows, and executive decision-making.
You might thrive in this role if you have:
Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability.
Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0 1.
Bonus if you have:
Experience building or scaling forecasting platforms in a high-growth company.
Familiarity with causal inference, Bayesian forecasting.
Experience building agentic decision support systems.
Passion for AI and a strong point of view on how machine learning should inform strategic decisions in fast-moving environments.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core the full spectrum of humanity.
We are an equal opportunity employeration, or other applicable legally protected characteristic.
Background checks for applicants will be administered in accordance with applicable lawation technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities.
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Compensation
$347K – $445K + Offers Equity
The base pay offered may vary depending on multiple individualized factorsance-related bonus(es) for eligible employees, and the following benefits.
Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible
Relocation support for eligible employees
Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
More details about our benefits are available to candidates during the hiring process.
This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
See All 89 Machine Learning Scientist Jobs in San Francisco
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Find JobsMachine Learning Scientist Job Market in San Francisco
Who's Hiring
- Lila Sciences23
- Genentech9
- Merge Labs9
- Achira6A
- Rad AI6
Top Industries Hiring
- Technology & Software20
- Biotechnology & Pharmaceuticals17
- Medical Devices3
- Artificial Intelligence3
- Banking & Financial Services3
Machine Learning Scientist Jobs in San Francisco: Frequently Asked Questions
How do I get a machine learning scientist job in San Francisco?
Focus your search on SoMa and Mission Bay, where the highest density of AI-native companies and established tech employers operate. San Francisco's market rewards candidates who can show production-grade model deployment, not just research credentials. Familiarity with LLMs, reinforcement learning, or computer vision gives a practical edge. Targeting mid-size AI startups alongside the larger platform companies broadens your options considerably.
Which companies hire machine learning scientists in San Francisco?
Companies currently hiring machine learning scientists in San Francisco include Lila Sciences, Genentech, and Merge Labs, per current listings on Migrate Mate as of November 2026. The San Francisco market draws a wide mix of AI research labs, cloud infrastructure providers, and well-funded Series B and C startups building foundation models or applied ML products.
Are there remote machine learning scientist jobs in San Francisco?
Yes, though hybrid is far more common than fully remote, since many San Francisco employers expect regular on-site collaboration on model development and experiments. About 54% of machine learning scientist openings tied to San Francisco are remote or hybrid as of November 2026, with most flexibility found in roles focused on model evaluation, data pipeline work, and applied research rather than core infrastructure.
How can I get a machine learning scientist job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is through an ML engineer or data scientist role at a mid-size startup, then transitioning into research as you build a portfolio of shipped models. San Francisco's dense startup ecosystem includes many companies willing to hire strong PhD candidates or bootcamp graduates for junior research roles. Contributing to open-source ML projects and presenting at local AI meetups in the Mission or Potrero Hill area also builds the local visibility that leads to referrals.
Which industries hire the most machine learning scientists in San Francisco?
The sectors hiring the most machine learning scientists in San Francisco are Technology & Software, Biotechnology & Pharmaceuticals, and Medical Devices, based on current listings on Migrate Mate as of November 2026. San Francisco's concentration of AI-first technology companies, digital health platforms, and fintech firms creates consistent demand across these sectors year-round.
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