Applied AI Engineer Jobs in California
Applied AI Engineer jobs in California are among the most actively recruited in the country, with demand concentrated in enterprise software, cloud infrastructure, autonomous systems, and health tech across experience levels from entry-level ML engineer to principal AI architect. The largest hiring metros are the San Francisco Bay Area, Los Angeles, and San Diego, where companies like Google, Meta, and Qualcomm maintain deep applied AI teams. The most sought-after specializations include large language model fine-tuning, real-time inference systems, and AI platform engineering. Find a role that fits below and apply directly.
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The Health Personalization team builds AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing. We harness large language models and the latest ML advances to build products that are useful, personal, privacy-preserving, and safe - turning research and incubation into features people rely on every day. As part of the larger Sensor Software & Prototyping team, we work across hardware platforms and data modalities including wearables and natural language input. We are committed to building deeply personal features that understand, anticipate, and adapt to users' behaviors and uphold Apple's deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
Description
In this role, you will prototype, develop, evaluate, and ship Generative AI experiences for real-world health and wellbeing applications. You'll apply strong ML fundamentals, build practical evaluation methods, and ground your work in real on-device user interactions. Your work will directly shape customer-facing health products across the full ML lifecycle.
A strong candidate makes progress through ambiguity - building, learning from real data, and iterating toward the right answer rather than waiting for the perfect plan. They take ownership of outcomes end-to-end, prioritize well, and learn fast.","responsibilities":"Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle - prototyping on-device experiences to explore design directions, and shipping production-quality features.
Independently design, run, and analyze ML experiments to deliver measurable quality improvements.
Design and implement evaluation frameworks - including automated assessment tools, LLM-based autograders, and benchmarks - to measure and improve model quality.
Analyze algorithm and feature behavior, identify failure modes, and drive actionable improvements through experimentation and failure analysis - verifying that fixes hold with data.
Work cross-functionally with many teams - including clinical experts, designers, and HW and SW teams, and more - to bring features into production with real-world applicability and impact.
Preferred Qualifications
MS or PhD in computer science, machine learning, health informatics, biomedical engineering, or a related quantitative field - or equivalent industry experience.
Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders.
Technical expertise in generative AI domains, such as large language model architectures, knowledge retrieval, and natural language understanding.
Deep expertise with LLM-based evaluation systems and evidence-based approaches to test development and quality measurement.
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products.
Experience building and deploying performant on-device or full-stack systems, including rapid prototyping of user-facing experiences (e.g. Swift, SwiftUI), is a plus.
Minimum Qualifications
BS and a minimum of 3 years relevant industry experience
Ability to leverage AI-assisted tooling to write clean, performant code (e.g. Python), while maintaining full ownership of code quality and software development best practices (e.g. Git).
Technical expertise and hands-on experience building and evaluating machine learning solutions for user-facing applications.
Comfort building functional prototypes or proof-of-concept demos to test ideas quickly.
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 201+ Applied AI Engineer Jobs in California
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Find Applied AI Engineer JobsApplied AI Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Applied AI Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- Anthropic20

- OpenAI16

- Amazon10

- Amazon Web Services9

- Meta6

Top Industries Hiring
- Technology & Software17
- Science & Research9
- Fintech2
- Banking & Financial Services2
- Cybersecurity1
What California Employers Look For
The qualifications that appear most often in applied AI engineer jobs across California.
- Bachelor's or master's degree in computer science, machine learning, or a related field
- Production experience deploying ML models using PyTorch, TensorFlow, or JAX
- Proficiency building and maintaining scalable ML pipelines and data workflows
- Hands-on experience with cloud platforms such as Google Cloud, AWS, or Azure
- Familiarity with LLM fine-tuning, prompt engineering, or retrieval-augmented generation
- Strong programming skills in Python and experience with MLOps tooling and CI/CD
Applied AI Engineer Jobs in California: Frequently Asked Questions
How do you become a applied ai engineer in California?
Applied AI engineering in California has no state-issued license, so the path runs through education and demonstrated technical skill. Most California employers expect a bachelor's degree in computer science, data science, or a closely related field, with a master's preferred at larger research-driven companies. Building a portfolio of deployed ML projects, contributing to open-source AI repositories, and completing industry-recognized credentials in deep learning or MLOps strengthens a candidacy considerably.
How much do applied AI engineers make in California?
Applied AI 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 applied ai engineers in California?
Employers hiring applied ai engineers in California right now include Anthropic, OpenAI, and Amazon, based on current listings on Migrate Mate as of November 2026. California's concentration of major tech headquarters, semiconductor firms, and AI-native startups makes it one of the broadest and most competitive applied AI hiring markets in the world.
Which California cities have the most applied ai engineer jobs?
The cities with the most applied ai engineer openings in California are San Francisco, Sunnyvale, and Santa Clara. The Bay Area leads because it is home to the headquarters of the largest AI research organizations and cloud platforms, while Los Angeles draws hiring from entertainment tech, autonomous vehicles, and enterprise software, and San Diego benefits from strong activity in defense technology and biotech.
Are there remote applied ai engineer jobs in California?
Yes, and more than most fields. About 69% of applied ai engineer openings tied to California are remote or hybrid as of November 2026, reflecting how much of the work involves code, experimentation, and collaboration through shared cloud environments. The most remote-friendly parts of the role are model development, research, and data pipeline work, while roles requiring on-device or edge-hardware integration tend to require in-person presence.
How can I get hired as a applied ai engineer in California with little or no experience?
The most realistic entry path is through a machine learning engineer or data scientist role at a California company that runs a structured new-grad program, with Google, Apple, and NVIDIA all running university-hire cohorts that place candidates into applied AI teams. Building and publishing end-to-end ML projects on GitHub, earning credentials like Google's Professional Machine Learning Engineer certification, and targeting AI-adjacent roles such as data engineer or ML infrastructure engineer are the concrete steps that open doors without prior industry experience.
Where can I find and apply to applied ai engineer jobs in California?
You can find and apply to applied ai engineer jobs in California on Migrate Mate, which lists current California openings updated regularly. Search the listings for roles that match your experience level and specialty, then apply directly to the ones that fit.
See All 201+ Applied AI Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
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