Machine Learning Manager Jobs in California
Machine Learning Manager jobs in California represent one of the most active and competitive markets in the country, with demand concentrated in enterprise software, cloud infrastructure, autonomous systems, and biotech across seniority levels from lead ML engineer stepping into management through senior director of machine learning. The highest volume of openings is in the San Francisco Bay Area, Los Angeles, and San Diego, where established employers such as Google, Apple, and Qualcomm consistently hire for these roles. The most sought-after specialties in California are large language model deployment, MLOps and model governance, and computer vision applied to healthcare or autonomous vehicles. Find a role that fits below and apply directly.
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The incredible potential of multimodal foundation models and large language models has unlocked machine learning applications that were previously thought infeasible. The Video Computer Vision (VCV) group is looking for a highly motivated and skilled Machine Learning Systems Engineer to help us ship cutting-edge computer vision technology on Apple devices.
The VCV organization has pioneered groundbreaking features like FaceID/FaceKit, Gaze/Hand Gesture Control, Body Tracking, and 2D/3D Scene Understanding fundamentally changing how millions of users interact with technology. We seamlessly balance research and product requirements to deliver pioneering, Apple-quality experiences. By innovating across the full stack and partnering closely with hardware, software, and AI teams, we shape future products and bring our architectural vision to life.
Description
As a member of the Video Computer Vision team, you will work across the stack to transform promising research projects into refined products that ship to our customers. You will build software infrastructure to deliver multimodal context to models and optimize the software harness and the model for efficient on-device deployment. Partnering closely with algorithm researchers, you will also participate in post-training model alignment and evaluation.","responsibilities":"Develop on-device software that bridges multimodal AI models and computer vision technologies with production systems deployed across Apple devices.
Optimize on-device inference latency, memory footprint, and computational efficiency of CV/ML models.
Benchmark, profile, and evaluate the power consumption and thermal performance of models running on Apple silicon.
Engage with cross-functional teams to understand and influence requirements, brainstorm the solution space, and propose, design and implement debuggable and maintainable Computer Vision systems meeting requirements.
Design experiments and evaluations to understand quality and on-device deployment tradeoffs, driving informed system design decisions.
Debug concurrent systems on embedded devices via a variety of existing tools and techniques; develop innovative debug tools and visualizations when existing ones don't fit the bill.
Preferred Qualifications
Programming experience with Swift and familiarity with CoreML, CoreFoundation, and RealityKit frameworks.
Fundamental knowledge of real-time video pipelines, image transformations, and rendering loops.
Experience optimizing models for neural network accelerators (e.g., Apple Neural Engine or mobile GPUs).
Minimum Qualifications
Bachelor’s degree in Computer Science, Machine Learning, or a related discipline, and 3+ years of relevant industry experience.
Strong ML fundamentals.
Proven track record of writing high-quality production code for shipped on-device CV/ML features deployed on embedded platforms
Solid understanding of operating system fundamentals and extensive programming experience in Python and C++.
Hands-on experience with PyTorch and familiarity with the end-to-end ML lifecycle (data preprocessing, training, evaluation, and edge deployment).
Experience with Supervised Fine-Tuning (SFT) pipelines to adapt vision and multimodal foundation models for specialized, on-device downstream tasks.
Robust foundational understanding of machine learning architectures, specifically Multimodal LLMs and the integration of ML components into complex production systems.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See All 714+ Machine Learning Manager Jobs in California
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Find Machine Learning Manager JobsMachine Learning Manager Jobs by City in California
Where California roles are concentrated, by current openings.
Machine Learning Manager Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- TikTok101

- Uber26

- Meta21

- ByteDance21

- ServiceNow21

Top Industries Hiring
- Technology & Software115
- Electronics & Hardware16
- Artificial Intelligence14
- Biotechnology & Pharmaceuticals12
- Science & Research10
What California Employers Look For
The qualifications that appear most often in machine learning manager jobs across California.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Five or more years of hands-on machine learning engineering or research experience
- Demonstrated experience managing or mentoring a team of ML engineers or data scientists
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or JAX
- Experience designing and shipping ML systems at production scale in cloud environments
- Strong cross-functional communication skills for partnering with product and engineering leadership
Machine Learning Manager Jobs in California: Frequently Asked Questions
How do you become a machine learning manager in California?
The most direct path is building several years of hands-on ML engineering or research experience and then transitioning into a team lead or staff engineer role before moving into management. California does not require a state-issued license for this role. Employers here consistently prioritize a graduate degree in computer science, applied mathematics, or a related field, along with a portfolio of shipped production ML systems and evidence of mentoring or technical leadership within a cross-functional team.
Which companies hire machine learning managers in California?
Employers hiring machine learning managers in California right now include TikTok, Uber, and Meta, based on current listings on Migrate Mate as of November 2026. California's concentration of major tech headquarters, defense contractors, and life sciences companies means hiring is unusually broad, covering both consumer-facing AI products and deep research environments.
Which California cities have the most machine learning manager jobs?
San Francisco, San Jose, and Sunnyvale have the most machine learning manager openings in California. The Bay Area dominates due to the density of major tech headquarters and AI-focused startups in San Francisco, Mountain View, and Sunnyvale, while Los Angeles draws openings from entertainment technology and aerospace firms, and San Diego's concentration of defense contractors and biotech companies sustains steady demand as well.
Are there remote machine learning manager jobs in California?
Yes, and more than most fields. About 52% of machine learning manager openings tied to California are remote or hybrid as of November 2026, reflecting how much of this work centers on code, model experimentation, and asynchronous collaboration rather than physical presence. The portions of the role most commonly done fully remotely are model evaluation, roadmap planning, and code review, while cross-functional alignment and team development often draw managers back on-site at least part of the week.
How can I get hired as a machine learning manager in California with little or no experience?
The most realistic entry path is securing an individual contributor ML engineering or data science role at a large California employer and pursuing an internal promotion into a lead or manager position. Companies such as Meta, Salesforce, and Adobe run structured rotation and mentorship programs that develop senior ICs into managers. Lateral moves from adjacent roles like data engineering manager or applied research scientist are common. A strong GitHub portfolio, a published model, or completion of an advanced degree from a UC system campus can accelerate that transition.
Where can I find and apply to machine learning manager jobs in California?
You can find and apply to machine learning manager jobs in California on Migrate Mate, which lists current California openings. Find a role that fits and apply directly from the listing.
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