AI ML Engineer Jobs in San Francisco, CA
AI ML Engineer jobs in San Francisco are concentrated in SoMa, Mission Bay, and the Financial District, with strong demand across enterprise software, biotech, and fintech. Employers posting right now include Genentech, Lila Sciences, and Uber. Scan the live roles below and apply to whichever ones fit.
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Atlassian is looking for a Senior Machine Learning Engineer to join our Search & Intelligence organization. We build AI-native experiences, agentic systems, models, evaluation frameworks, and data platforms that power Atlassian’s AI products.
Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Responsibilities:Your role and impact
You will develop and productionize machine learning systems for search, retrieval, ranking, conversational experiences, and AI agents. You will own projects across the ML lifecycle, from problem definition and data development through experimentation, evaluation, deployment, and continuous improvement.
A key part of this role is making evaluation a first-class part of AI development. You will help define quality, build evaluation datasets and benchmarks, analyze model behavior, and use results to guide product and engineering decisions.
You will collaborate with product managers, software engineers, data scientists, research scientists, and platform teams. You will independently solve complex problems, contribute to technical direction, and mentor other engineers.
What you’ll do
Build and productionize machine learning models and AI systems for Search & Intelligence products.
Own projects from concept through deployment, monitoring, evaluation, and iteration.
Develop AI-native experiences across search, retrieval, ranking, recommendations, conversational systems, and agentic workflows.
Design evaluation-driven development processes, including quality metrics, test cases, benchmarks, and acceptance criteria.
Build evaluation datasets, regression suites, and pipelines for search, RAG, chat, and agentic systems.
Conduct offline and online evaluations, human assessments, model-based evaluations, and error analysis.
Design scalable architectures that meet requirements for quality, reliability, latency, privacy, and cost.
Apply modern techniques in information retrieval, ranking, embeddings, NLP, deep learning, and large language models.
Communicate technical decisions and results clearly across technical and non-technical audiences.
Mentor engineers and contribute to engineering and ML best practices.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges:In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
Qualifications:On your first day, we’ll expect you to have
A Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience.
At least 4 years of experience developing and deploying machine learning or AI systems in production.
Strong Python skills and experience with Java, Kotlin, TypeScript, or another production language.
Experience with SQL and large-scale data processing technologies such as Spark.
Experience building, evaluating, deploying, and scaling models with large datasets.
Experience designing evaluation strategies, analyzing model quality, and using results to guide improvements.
Familiarity with cloud-based ML and data platforms such as AWS or Databricks.
Ability to independently solve ambiguous problems and deliver practical, production-quality solutions.
Strong communication and collaboration skills.
An agile mindset and commitment to continuous improvement.
It’s great, but not required, if you have
Experience building AI-native products, RAG systems, conversational assistants, or tool-using agents.
Experience with evaluation-driven development, benchmarks, regression testing, human evaluation, or LLM-as-a-judge.
Experience evaluating agent planning, tool use, task completion, or multi-step reasoning.
Experience with search relevance, ranking, recommendations, personalization, embeddings, or NLP.
Experience fine-tuning, post-training, evaluating, or optimizing large language models.
Experience with ML platforms, model serving, data pipelines, observability, or responsible AI.
Experience mentoring engineers or influencing technical direction within a team.
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh.
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
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Find AI ML Engineer JobsAI ML Engineer Job Market in San Francisco
Who's Hiring
- Genentech14

- Lila Sciences14

- Uber10

- Achira10A
- Samsara5

Top Industries Hiring
- Technology & Software10
- Electronics & Hardware10
- Automotive5
- Banking & Financial Services5
- Healthcare & Medical Services5
AI ML Engineer Jobs in San Francisco: Frequently Asked Questions
How do I get a ai ml engineer job in San Francisco?
Focus on San Francisco's dominant hiring clusters: enterprise software companies in SoMa, biotech and life sciences firms in Mission Bay, and fintech players in the Financial District. Hands-on experience with large language models, MLOps pipelines, or production model deployment gives candidates a clear edge here. Contributing to open-source ML projects and attending local meetups in the Bay Area tech community also puts your work in front of the hiring teams that matter most.
Which companies hire ai ml engineers in San Francisco?
San Francisco ai ml engineer roles are posted by Genentech, Lila Sciences, and Uber and others right now, based on current listings on Migrate Mate as of September 2026. The city draws a wide mix of well-funded startups, established tech platforms, and healthcare and fintech companies that have made AI infrastructure a core part of their product teams.
Are there remote ai ml engineer jobs in San Francisco?
Yes, ai ml engineer work is well-suited to remote and hybrid arrangements since most of the role involves coding, model training, and data work that does not require a physical presence. About 75% of ai ml engineer openings tied to San Francisco are remote or hybrid as of September 2026, reflecting how tech-forward local employers approach this function. Research, experimentation, and evaluation tasks tend to be the most remote-friendly parts of the role in San Francisco.
How can I get a ai ml engineer job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is through a junior ML engineer or data scientist role at a growth-stage startup in SoMa or the broader Bay Area tech ecosystem, where smaller teams are more open to candidates still building production experience. Internships at biotech firms in Mission Bay or AI-focused product teams at mid-size software companies are strong lateral moves. A portfolio of deployed model projects on GitHub, even at small scale, carries significant weight with San Francisco hiring managers reviewing early-career candidates.
Which industries hire the most ai ml engineers in San Francisco?
Most ai ml engineer openings in San Francisco sit in Technology & Software, Electronics & Hardware, and Automotive, per current listings on Migrate Mate as of September 2026. San Francisco's role as the global center of AI investment means these sectors compete intensely for ML talent, driving consistent demand across both established companies and well-capitalized startups.
Related Jobs in California
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