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 Uber, DoorDash, and Pinterest. Scan the live roles below and apply to whichever ones fit.
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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:As part of our team, you will play a crucial role in innovating the core intelligence solutions within our DevAI products. Your responsibilities will include (but not limited to) LLM integration, prompt engineering, and developing end-to-end AI features using cutting-edge technologies. You will collaborate closely with a diverse and highly skilled group of scientists and software engineers within our team, as well as with multiple partner teams across the company. Together, we are committed to delivering Atlassian’s world-class developer AI products that will shape the future of software development.
Responsibility
General Responsibilities
These are ongoing or overarching tasks that guide the strategic and collaborative aspects of the role:
Problem Solving: Identify complex challenges and provide creative solutions to advance the capabilities and functionalities of the products.
Collaboration: Work with cross-functional teams, including data scientists and software engineers. Build and maintain sustainable partnerships with team members from various technical backgrounds.
Communication: Communicate technical details effectively to the team and engage in technical discussions to contribute ideas and solutions.
Continuous Learning: Stay updated with the latest research and advancements in machine learning, AI, and relevant technology applications. Apply cutting-edge knowledge and techniques to enhance product innovation and effectiveness.
Daily Responsibilities
These tasks are more routine or technical, involving hands-on activities that need to be performed regularly:
Design and Development: Design LLM based methodology and algorithms tailored to specific product needs.
Data Handling: Perform data preprocessing and feature engineering to improve product inputs and performance.
Evaluation: Conduct experiments to evaluate the performance of products and use a variety of metrics and testing methods to ensure the solutions meet design specifications.
Implementation and Optimization: Implement and optimize machine learning pipelines.
Monitoring and Maintenance the deployed intelligence solutions to ensure they continue to perform accurately and efficiently.
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: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
Qualifications: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 JobsMachine Learning Engineer Job Market in San Francisco
Who's Hiring
- Uber48

- DoorDash44

- Pinterest39

- OpenAI30

- Anthropic30

Top Industries Hiring
- Technology & Software161
- Science & Research30
- Artificial Intelligence26
- Banking & Financial Services22
- Electronics & Hardware13
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 Uber, DoorDash, and Pinterest, based on current listings on Migrate Mate as of November 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 68% of machine learning engineer openings tied to San Francisco are remote or hybrid as of November 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 Artificial Intelligence, per current listings on Migrate Mate as of November 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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