Machine Learning Engineer Jobs in San Francisco, CA
Machine Learning Engineer jobs in San Francisco concentrate in SoMa, Mission Bay, and the Financial District, driven by demand from AI research labs, enterprise software companies, and fintech platforms, with specializations in NLP, computer vision, and MLOps among the most sought-after. Employers hiring right now include DoorDash, Uber, and OpenAI. Scan the live roles below and apply to whichever ones fit.
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Operating across key business areas like grocery and food, the Consumer Incentives team drives Uber's growth and long-term profitability. We build products that power seamless, affordable, and enjoyable customer experiences by building sophisticated distributed systems and AI-powered optimizations to scale products for hundreds of millions of global users.
What you'll do
In this role, you will build products powered by scalable distributed systems and advanced AI solutions. Your work will optimize user experiences across multiple verticals, such as grocery and food, while fostering sustainable business growth. Key responsibilities include:
- Architecting and launching products to power key consumer experience and business outcomes.
- Overseeing full project lifecycles spanning initial scoping, offline evaluation, experimental testing, production deployment, and post-launch maintenance.
- Designing, tuning, and enhancing systems and algorithms to operate at scale.
- Partnering with cross-functional stakeholders across product management, operations, and data science.
- Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 4+ years of full-time engineering experience.
- Proficiency in at least one programming language such as Python, Go, or Java
- Experience in building and productionizing innovative end-to-end ML systems.
- Strong communication skills and ability to work effectively with cross-functional partners
- Strong sense of ownership to drive projects end-to-end
- Track record of designing and delivering large-scale consumer products
- Demonstrated leadership skills, with experience in mentoring and guiding junior engineers. Proven experience in experimental design and causal inference
For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
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Find JobsMachine Learning Engineer Job Market in San Francisco
Who's Hiring
- Pinterest76

- DoorDash64

- Uber47

- OpenAI41

Top Industries Hiring
- Technology & Software252
- Science & Research53
- Electronics & Hardware35
- Banking & Financial Services29
- Biotechnology & Pharmaceuticals23
Machine Learning Engineer Jobs in San Francisco: Frequently Asked Questions
How do I get a machine learning engineer job in San Francisco?
Focus your search on San Francisco's dense clusters of AI-native startups in SoMa, enterprise tech companies in the Financial District, and biotech firms in Mission Bay, since those sectors drive the bulk of local openings. Candidates who can demonstrate production ML experience, not just research, stand out here. Contributing to open-source projects and engaging with the Bay Area's active ML meetup and conference scene also builds the kind of local visibility that leads to referrals.
Which companies hire machine learning engineers in San Francisco?
Employers hiring machine learning engineers in San Francisco right now include DoorDash, Uber, and OpenAI, based on current listings on Migrate Mate as of September 2026. San Francisco's hiring landscape skews toward AI-first startups, large consumer tech platforms, and fintech companies with dedicated ML infrastructure teams.
Are there remote machine learning engineer jobs in San Francisco?
Yes, though many roles tied to San Francisco require on-site collaboration, particularly those involving proprietary hardware, research labs, or cross-functional product teams. About 66% of machine learning engineer openings tied to San Francisco are remote or hybrid as of September 2026, reflecting a market that still values in-person work for certain stages of the ML lifecycle. Pure modeling, data pipeline, and MLOps roles tend to offer the most remote flexibility locally.
How can I get a machine learning engineer job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is through an ML engineer internship or a junior data scientist role at a mid-size startup in SoMa or Mission Bay, where smaller teams give early-career candidates broader exposure than large tech companies typically do. Building a portfolio of end-to-end projects, including data ingestion, model training, and deployment, matters more to San Francisco hiring managers than credentials alone. Bootcamp graduates who can demonstrate working production code and contribute to open-source repositories have found traction at growth-stage companies across the city.
Which industries hire the most machine learning engineers in San Francisco?
Most machine learning engineer openings in San Francisco sit in Technology & Software, Science & Research, and Electronics & Hardware, per current listings on Migrate Mate as of September 2026. San Francisco's concentration of AI research investment, consumer tech scale, and fintech infrastructure makes those sectors the primary engines of local ML hiring.
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