AI Platform Engineer Jobs in California
AI Platform Engineer jobs in California represent one of the most active and competitive markets in the country, concentrated in cloud infrastructure, enterprise AI, and machine learning operations roles at every level from associate to principal engineer. The heaviest hiring is in San Francisco, San Jose, and Los Angeles, where companies like Google, Meta, and Salesforce maintain large engineering organizations with dedicated AI platform teams. The most in-demand specialties are MLOps pipeline development, LLM infrastructure, and distributed systems engineering. Find a role that fits below and apply directly.
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Showing 5 of 213+ AI Platform Engineer jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in software engineering leadership in ML Infrastructure, ML, or product-focused AI.
- 5 years of experience with large scale distributed systems.
- 2 years of experience in a people management or team leadership role.
- Experience with Generative AI lifecycle, including Agent frameworks or protocols (e.g., MCP, A2A), RAG, prompt engineering, or model evaluation systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Demonstrated experience architecting or contributing to simulation frameworks, evaluation infrastructure, or enterprise quality platforms.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Gemini Cloud Assist is designed to simplify how customers learn, design, deploy, and operate their services. Our goal is to establish intelligent AI agent as a primary interface for cloud operations, integrating seamlessly across the Cloud Console, IDEs, and other developer surfaces. In this role, you will focus on the Quality Flywheel, a foundational platform at the core of our AI quality strategy. You will build the end-to-end system that drives our agent’s continuous, automated improvement. This involves analyzing user interactions, implementing real-time evaluations to detect successes and failures, generating high-quality evaluation data, and creating feedback loops that drive model self-improvement and fine-tuning.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead a team of engineers, driving career growth, team culture, and execution across data collection, evaluation generation, and unified benchmarks.
- Act as Tech Lead for the Quality Flywheel, architecting systems for scalable data collection, realistic simulation environments, eval generation, and online hill climbing.
- Direct software design and implementation for next-gen evaluation infrastructure (Eval Infra), tooling, and Gemini post-training systems adhering to architectural best practices.
- Partner across teams to distill complex, ambiguous model and platform requirements into simplified, robust technical solutions.
- Drive overarching testing and reliability architecture, advocating production stability, test environment improvements, and on-call operational support.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in software engineering leadership in ML Infrastructure, ML, or product-focused AI.
- 5 years of experience with large scale distributed systems.
- 2 years of experience in a people management or team leadership role.
- Experience with Generative AI lifecycle, including Agent frameworks or protocols (e.g., MCP, A2A), RAG, prompt engineering, or model evaluation systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Demonstrated experience architecting or contributing to simulation frameworks, evaluation infrastructure, or enterprise quality platforms.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Gemini Cloud Assist is designed to simplify how customers learn, design, deploy, and operate their services. Our goal is to establish intelligent AI agent as a primary interface for cloud operations, integrating seamlessly across the Cloud Console, IDEs, and other developer surfaces. In this role, you will focus on the Quality Flywheel, a foundational platform at the core of our AI quality strategy. You will build the end-to-end system that drives our agent’s continuous, automated improvement. This involves analyzing user interactions, implementing real-time evaluations to detect successes and failures, generating high-quality evaluation data, and creating feedback loops that drive model self-improvement and fine-tuning.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead a team of engineers, driving career growth, team culture, and execution across data collection, evaluation generation, and unified benchmarks.
- Act as Tech Lead for the Quality Flywheel, architecting systems for scalable data collection, realistic simulation environments, eval generation, and online hill climbing.
- Direct software design and implementation for next-gen evaluation infrastructure (Eval Infra), tooling, and Gemini post-training systems adhering to architectural best practices.
- Partner across teams to distill complex, ambiguous model and platform requirements into simplified, robust technical solutions.
- Drive overarching testing and reliability architecture, advocating production stability, test environment improvements, and on-call operational support.
See All 213+ AI Platform Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find AI Platform Engineer JobsAI Platform Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
AI Platform Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- TikTok12
- Capital One11
- Apple6
- University of San Diego6
- Google5
Top Industries Hiring
- Technology & Software18
- Electronics & Hardware4
- Science & Research3
- Artificial Intelligence3
- Insurance2
What California Employers Look For
The qualifications that appear most often in AI platform engineer jobs across California.
- Bachelor's or master's degree in computer science, software engineering, or a related technical field
- Hands-on experience building and maintaining ML pipelines using tools such as Kubeflow, MLflow, or Ray
- Proficiency with cloud platforms including Google Cloud, AWS, or Azure in production AI environments
- Strong programming skills in Python and familiarity with containerization using Docker and Kubernetes
- Experience with large-scale distributed systems, data engineering, and model deployment infrastructure
- Familiarity with CI/CD practices and infrastructure-as-code tools such as Terraform or Pulumi
AI Platform Engineer Jobs in California: Frequently Asked Questions
How do you become a ai platform engineer in California?
Most California employers expect a bachelor's degree in computer science, software engineering, or a related discipline, though a master's degree is increasingly common at larger tech firms. There is no state-issued license for this role in California. Candidates strengthen their profile by earning cloud certifications from providers like Google or AWS, building a portfolio of deployed ML systems, and gaining hands-on experience through internships or open-source contributions to AI infrastructure projects.
How much do AI platform engineers make in California?
AI platform engineers in California earn a median of about $134,440 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $58,340 for the lowest 10% to over $222,690 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai platform engineers in California?
Employers hiring ai platform engineers in California right now include TikTok, Capital One, and Apple, based on current listings on Migrate Mate as of November 2026. California's concentration of cloud-native technology companies and enterprise software headquarters means demand runs consistently across both large established firms and well-funded growth-stage companies throughout the Bay Area and Los Angeles.
Which California cities have the most ai platform engineer jobs?
San Francisco, San Jose, and San Diego have the most ai platform engineer openings in California. San Francisco and San Jose dominate because they sit at the center of the Bay Area technology ecosystem, home to the headquarters of major cloud, AI, and enterprise software companies, while Los Angeles has grown significantly as a hub for media-tech, fintech, and consumer AI firms driving their own platform infrastructure needs.
Are there remote ai platform engineer jobs in California?
Yes, and more than most fields. About 63% of ai platform engineer openings tied to California are remote or hybrid as of November 2026, reflecting how much of this work involves cloud systems and code rather than on-site hardware. Infrastructure design, pipeline development, and model monitoring tasks are the most commonly performed remotely, though some roles at larger firms require on-site collaboration for security or compliance reasons.
How can I get hired as a ai platform engineer in California with little or no experience?
The most realistic entry path is moving from a software engineering or data engineering role into AI platform work by picking up MLOps tooling on the job or through project work. Large California technology employers often post associate or junior platform engineer roles that accept candidates with cloud fundamentals and Python skills over deep ML experience. Building and publishing an end-to-end ML pipeline project on a public repository, earning a Google Cloud or AWS certification, and targeting companies with established new-grad programs in the Bay Area gives candidates without a formal AI background a concrete edge.
Where can I find and apply to ai platform engineer jobs in California?
You can find and apply to ai platform engineer jobs in California on Migrate Mate, which lists current California openings across the state. Find the roles that fit your experience and location and apply directly to the employers posting them.
See All 213+ AI Platform Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find AI Platform Engineer Jobs