ML Software Engineer Jobs in California
ML Software Engineer jobs in California represent one of the most active and competitive markets in the country, concentrated in tech product development, AI research, autonomous systems, and enterprise software across seniority levels from entry-level to principal and staff engineer. The heaviest hiring is in the San Francisco Bay Area, Los Angeles, and San Diego, where companies like Google, Apple, and Qualcomm maintain large engineering organizations with dedicated machine learning teams. The most in-demand specialties are large language model fine-tuning, computer vision, and MLOps infrastructure. Find a role that fits below and apply directly.
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Showing 5 of 118+ ML Software Engineer jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 2 years of experience developing compilers.
- Experience in mobile development.
Preferred qualifications:
- Experience leading and delivering successful ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
- Experience in ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Experience with on-device ML software development kits (SDKs)/tooling (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
- Understanding of Generative AI model architectures and their optimization for on-device execution.
- Excellent communication and collaboration skills.
- Passion for innovation and a strong desire to push the boundaries of what's possible with on-device ML.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
LiteRT is Google’s next generation on-device AI framework, succeeding TensorFlow Lite (TFLite). It is designed to maximize the performance, efficiency, and portability of ML models on a wide array of edge devices, from mobile phones to embedded systems. LiteRT significantly upgrades GPU acceleration and introduces native NPU acceleration, while maintaining and enhancing the robust CPU performance inherited from TFLite.
LiteRT enables developers and Google products to deploy AI across mobile, web, desktop, and embedded. Our team focuses on building cross-platform infrastructure aligned with Google's business needs, serving top Google products (Android, Chrome, Photos, Meet, Youtube, etc), third-party developers, and specialized Pixel solutions. Our goal is to provide on-device AI infrastructure with exceptional performance, enabling framework and device flexibility at scale.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
- Develop LiteRT, Google's on-device AI framework for first- and third-party, enabling state-of-the-art (SOTA) hardware acceleration and use cases on edge platforms.
- Enable on-device deployment of key models, such as Gemini Nano and Gemma, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, iOS, desktop, and more.
- Improve performance of on-device model inference via optimizations in the model symbol, on-device runtime and kernel implementation.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 2 years of experience developing compilers.
- Experience in mobile development.
Preferred qualifications:
- Experience leading and delivering successful ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
- Experience in ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Experience with on-device ML software development kits (SDKs)/tooling (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
- Understanding of Generative AI model architectures and their optimization for on-device execution.
- Excellent communication and collaboration skills.
- Passion for innovation and a strong desire to push the boundaries of what's possible with on-device ML.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
LiteRT is Google’s next generation on-device AI framework, succeeding TensorFlow Lite (TFLite). It is designed to maximize the performance, efficiency, and portability of ML models on a wide array of edge devices, from mobile phones to embedded systems. LiteRT significantly upgrades GPU acceleration and introduces native NPU acceleration, while maintaining and enhancing the robust CPU performance inherited from TFLite.
LiteRT enables developers and Google products to deploy AI across mobile, web, desktop, and embedded. Our team focuses on building cross-platform infrastructure aligned with Google's business needs, serving top Google products (Android, Chrome, Photos, Meet, Youtube, etc), third-party developers, and specialized Pixel solutions. Our goal is to provide on-device AI infrastructure with exceptional performance, enabling framework and device flexibility at scale.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
- Develop LiteRT, Google's on-device AI framework for first- and third-party, enabling state-of-the-art (SOTA) hardware acceleration and use cases on edge platforms.
- Enable on-device deployment of key models, such as Gemini Nano and Gemma, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, iOS, desktop, and more.
- Improve performance of on-device model inference via optimizations in the model symbol, on-device runtime and kernel implementation.
See All 118+ ML Software Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find ML Software Engineer JobsML Software Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
ML Software Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- Meta15
- Apple14
- Google9
- Nuro6
- Zoox5
Top Industries Hiring
- Technology & Software27
- Electronics & Hardware12
- Automotive6
- Science & Research3
- Banking & Financial Services3
What California Employers Look For
The qualifications that appear most often in ML software engineer jobs across California.
- Bachelor's or master's degree in computer science, electrical engineering, or a related technical field
- Proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow
- Experience designing and deploying production ML models at scale
- Familiarity with cloud platforms such as Google Cloud, AWS, or Azure for model training and serving
- Strong foundation in statistics, linear algebra, and algorithm design
- Experience with MLOps tooling including experiment tracking, model versioning, and CI/CD pipelines
ML Software Engineer Jobs in California: Frequently Asked Questions
How do you become a ml software engineer in California?
There is no state-issued license or board registration required to work as a ml software engineer in California. The typical path is a bachelor's or master's degree in computer science, statistics, or a related field, followed by building a portfolio of end-to-end ML projects. California employers, particularly in the Bay Area and Los Angeles, strongly favor candidates who can demonstrate deployed model experience, contributions to open-source ML projects, or completion of research published alongside coursework.
How much do ML software engineers make in California?
ML software 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 ml software engineers in California?
Employers hiring ml software engineers in California right now include Meta, Apple, and Google, based on current listings on Migrate Mate as of August 2026. California's concentration of AI-focused product companies, semiconductor firms, and large-scale consumer platforms makes it one of the deepest hiring pools for this role anywhere in the country.
Which California cities have the most ml software engineer jobs?
Sunnyvale, Mountain View, and San Francisco have the most ml software engineer openings in California. The Bay Area dominates because of its density of AI-native companies, research labs, and major tech headquarters, while Los Angeles is driven by entertainment technology, autonomous vehicle programs, and a growing startup ecosystem, and San Diego sees consistent demand from defense contractors and Qualcomm's semiconductor and wireless AI division.
Are there remote ml software engineer jobs in California?
Yes, and more than most fields. About 52% of ml software engineer openings tied to California are remote or hybrid as of August 2026, reflecting how well this work translates to distributed teams. Model research, experimentation, and data pipeline development are the most frequently offered in fully remote arrangements, while roles tied to on-site hardware, robotics, or lab infrastructure tend to require in-person presence.
How can I get hired as a ml software engineer in California with little or no experience?
The most realistic entry path is securing an associate or junior ML engineer role, often titled ML engineer I or research engineer, at a mid-size California tech company after completing a master's program with a thesis or project involving real data and model deployment. Large California employers like Google and Meta run structured new-grad programs that recruit directly from university research labs. Candidates transitioning from adjacent roles such as data analyst, data scientist, or software engineer strengthen their candidacy with a public portfolio of trained models, an ML specialization certificate, or a research paper co-authored with a university supervisor.
Where can I find and apply to ml software engineer jobs in California?
You can find and apply to ml software engineer jobs in California on Migrate Mate, which lists current California openings from employers actively hiring for this role. Find roles that fit your experience level and location preference and apply directly.
See All 118+ ML Software Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find ML Software Engineer Jobs