Machine Learning Engineer Jobs in California
Machine Learning Engineer jobs in California are among the most active in the country, concentrated in technology, healthcare AI, autonomous systems, and financial services, with openings from entry-level ML engineer through principal and staff-level roles. The heaviest hiring is in the San Francisco Bay Area, Los Angeles, and San Diego, where companies like Google, Meta, and Qualcomm maintain major engineering operations. Computer vision, natural language processing, and large language model fine-tuning are the sub-areas drawing the most consistent demand across California employers. 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.
See All 866+ Machine Learning Engineer Jobs in California
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Find JobsMachine Learning Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Machine Learning Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- TikTok105

- Meta27

- Uber27

- Amazon Web Services23

- Google22

Top Industries Hiring
- Technology & Software145
- Electronics & Hardware26
- Science & Research17
- Artificial Intelligence17
- Automotive14
What California Employers Look For
The qualifications that appear most often in machine learning engineer jobs across California.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and core ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud ML infrastructure on AWS, Google Cloud, or Azure
- Strong foundation in linear algebra, probability, statistics, and optimization techniques
- Experience with data pipelines, feature engineering, and large-scale distributed computing tools
Machine Learning Engineer Jobs in California: Frequently Asked Questions
How do you become a machine learning engineer in California?
Machine learning engineering has no state-issued license in California, so the path runs through education and demonstrated technical skills. Most California employers expect at least a bachelor's degree in computer science, mathematics, or a related field, with a master's degree preferred at many Bay Area and Los Angeles tech companies. Building a portfolio of deployed projects, contributing to open-source ML work, and completing graduate coursework at UC Berkeley, Stanford, or UCLA strengthens a candidate's profile considerably.
How much do machine learning engineers make in California?
Machine learning engineers in California earn a median of about $174,410 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $105,060 for the lowest 10% to over $272,670 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire machine learning engineers in California?
Employers hiring machine learning engineers in California right now include TikTok, Meta, and Uber, based on current listings on Migrate Mate as of November 2026. California's concentration of technology headquarters, AI research labs, and defense contractors means consistent openings across a wide range of industries and seniority levels.
Which California cities have the most machine learning engineer jobs?
San Francisco, San Jose, and Mountain View have the most machine learning engineer openings in California. The Bay Area's density of technology headquarters and AI research organizations drives the largest share of listings, while Los Angeles draws demand from entertainment technology, aerospace, and a fast-growing startup ecosystem, and San Diego's strength in wireless technology and biotech creates a reliable secondary market.
Are there remote machine learning engineer jobs in California?
Yes, and more than most fields. About 52% of machine learning engineer openings tied to California are remote or hybrid as of November 2026, reflecting how well the core work, model development, experimentation, and code review, translates to distributed teams. Roles involving on-site GPU infrastructure management or close collaboration with hardware teams tend to require in-person presence more often than pure research or modeling positions.
How can I get hired as a machine learning engineer in California with little or no experience?
The most realistic entry path is through a machine learning or data science internship at a California technology company, many of which, including major Bay Area firms, run structured university recruiting programs targeting new graduates from UC campuses, Cal Poly, and California State University programs. Transitioning from a data analyst, software engineer, or research assistant role is a common lateral move. Building a GitHub portfolio with end-to-end ML projects and completing a relevant graduate certificate from a California institution significantly improves early-career competitiveness.
Where can I find and apply to machine learning engineer jobs in California?
You can find and apply to machine learning engineer jobs in California on Migrate Mate, which lists current California openings across industries and seniority levels. Find roles that fit your background and apply directly.
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