Machine Learning Jobs in California
Machine Learning jobs in California are among the most active in the country, with strong demand across big tech, autonomous systems, biotech, and financial services at every level from entry-level ML engineer through principal researcher and director of AI. The largest concentrations of openings are in the San Francisco Bay Area, Los Angeles, and San Diego, where employers like Google, Apple, and Qualcomm maintain deep and ongoing machine learning hiring programs. Model deployment, natural language processing, and computer vision are the specialties driving the most consistent demand across California's tech and life sciences corridors. Find a role that fits below and apply directly.
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Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Do you want to make Siri and Apple products smarter for our users? The MLPT & Infra teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup.
Description
As part of this group, you will build the storage and compute foundation behind one of the most exciting high-performance computing environments: trillions of records, petabytes of data, and the systems that turn them into search and Apple Intelligence experiences that delight our customers every day.","responsibilities":"Design and build our web signal store, a petabyte-scale Parquet/Iceberg lakehouse holding trillions of web documents and signals.
Design and build our in-house MapReduce-style processing framework, which runs thousands of workers on Kubernetes.
Improve performance, reliability, and cost at trillion-row scale, from read/write throughput and compaction to fault-tolerant batch jobs on shared clusters.
Own production health, including monitoring, on-call, and root-cause fixes, and raise the engineering bar through design and code reviews.
Preferred Qualifications
Deep familiarity with columnar and lakehouse formats (Parquet, Iceberg), and the judgment to choose between them at scale
Experience with storage internals: compaction, metadata and manifest management, indexing, and query performance tuning
Experience with workflow orchestration (e.g., Argo) and resource scheduling on shared Kubernetes clusters
Experience with key-value or online serving stores (e.g., Bigtable, HBase, Cassandra) and multi-cloud data movement
Experience with search indexing, machine learning, or NLP is a plus
Minimum Qualifications
Strong coding skills and a solid computer science background in algorithms, data structures, and distributed systems
5+ years experience designing, building, and operating large-scale distributed systems such as databases, storage platforms, or data processing frameworks
Hands-on experience with petabyte-scale batch data processing (MapReduce, Spark, or similar)
Proficiency in cloud-native architectures and compute orchestration on AWS (S3, EC2, EKS) and Kubernetes
Excellent interpersonal skills, with the ability to work independently and drive cross-team efforts
MS or PhD in Computer Science or related field
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 $216,200 and $324,800, 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.
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Find Machine Learning JobsMachine Learning Jobs by City in California
Where California roles are concentrated, by current openings.
Machine Learning Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- TikTok104

- Meta34

- Amazon Web Services31

- Uber29

- Google27

Top Industries Hiring
- Technology & Software153
- Electronics & Hardware29
- Artificial Intelligence20
- Biotechnology & Pharmaceuticals19
- Science & Research17
What California Employers Look For
The qualifications that appear most often in machine learning jobs across California.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Proficiency in Python and core ML frameworks such as TensorFlow, PyTorch, or JAX
- Experience designing, training, and evaluating supervised and unsupervised learning models
- Familiarity with cloud infrastructure on AWS, Google Cloud, or Azure for model deployment
- Ability to work with large-scale datasets, including data cleaning, feature engineering, and pipeline automation
- Strong communication skills to present model results and tradeoffs to cross-functional stakeholders
Machine Learning Jobs in California: Frequently Asked Questions
How do you become a machine learning engineer in California?
Machine learning roles in California do not require a state-issued license. Most employers expect at minimum a bachelor's degree in computer science, mathematics, or statistics, with a master's or PhD preferred for research-focused positions. California employers consistently prioritize demonstrated project experience, so building a portfolio of end-to-end ML projects on public repositories carries significant weight during screening and is often more decisive than credentials alone.
Which companies hire machine learnings in California?
Employers hiring machine learnings in California right now include TikTok, Meta, and Amazon Web Services, based on current listings on Migrate Mate as of November 2026. California's concentration of large tech headquarters, defense contractors, and well-funded biotech firms means machine learning hiring is distributed across multiple industries rather than concentrated in a single sector.
Which California cities have the most machine learning jobs?
San Francisco, San Jose, and Mountain View account for the largest share of machine learning openings in California. The Bay Area's density of major tech headquarters and AI-focused startups drives the volume there, while Los Angeles reflects growth in media tech, autonomous vehicles, and aerospace, and San Diego's openings are anchored by defense contractors and biotech research firms with active ML programs.
Are there remote machine learning jobs in California?
Yes, and more than most fields. About 52% of machine learning openings tied to California are remote or hybrid as of November 2026, reflecting how well the work translates to distributed teams. Research, modeling, and experimentation work tends to be the most remote-compatible, while roles involving hardware integration, lab datasets, or real-time inference infrastructure more often require on-site presence.
How can I get hired as a machine learning engineer in California with little or no experience?
The most realistic entry path is an internship or new-grad rotational program at a California tech employer. Companies like Google, Meta, and NVIDIA run structured new-grad programs specifically for candidates with strong academic projects but limited professional experience. Building two or three complete ML projects, including data sourcing, model training, and evaluation, and publishing them publicly provides concrete evidence of capability. Adjacent roles like data analyst, software engineer, or research assistant at California universities and national labs also serve as common transition points into machine learning.
Where can I find and apply to machine learning jobs in California?
You can find and apply to machine learning jobs in California on Migrate Mate, which lists current California openings across industries and experience levels. Find the roles that fit your background and apply directly from each listing.
See All 945+ Machine Learning Jobs in California
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