AI Research Engineer Jobs in California
AI Research Engineer jobs in California represent one of the most active and competitive markets in the country, concentrated in machine learning infrastructure, large language model development, computer vision, and AI safety across technology companies, biotech firms, and defense contractors at every level from entry-level research associate through principal researcher. The largest hiring metros are the San Francisco Bay Area, Los Angeles, and San Diego, where employers like Google, Meta, and Qualcomm maintain deep research operations. Demand is especially strong for engineers specializing in foundation model training, reinforcement learning, and applied AI systems. Find a role that fits below and apply directly.
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About Tolmo
Tolmo is cybersecurity for the age of AI. Coding agents now ship software faster than any human team can review or secure it; 100+ pull requests per engineer per week is no longer an outlier, and attackers are using the same agents to find and exploit weaknesses in days, not months. The old playbook of quarterly pentests and endless alert queues breaks at this speed.
We're building a new security playbook. Tolmo runs a fleet of AI security agents that reason over a live graph of your entire production system (code, CI, cloud, and telemetry) and continuously attack a faithful copy of it like a real adversary. Every finding arrives validated, with its blast radius and a remediation plan that lands in your workflow, ready for a coding agent to fix. Hours to integrate, days to your first validated finding.
We've done this before: Tolmo's founders built Sqreen (acquired by Datadog) and led security products that thousands of organizations trusted. We're backed by Accel and Y Combinator and just getting started.
The role
Our product is only as good as our agents' judgment. As a Research Engineer on AI Security, you make that judgment better and measurably so: how our agents plan, reason over a graph of a customer's production system, decide what is worth testing, and know when a finding is real.
This sits between research and engineering. In one week you might design an eval that catches a new class of false positive, change how an agent plans a multi-step investigation, compare models on a hard benchmark, and harden the agents themselves against prompt injection from the systems they inspect. You'll work directly with the founders, our engineers, and the security leads who run pentests with our agents, and your work ships to production.
What you'll do
Agent reasoning: improve how our agents plan, use tools, and reason over a live graph of code, cloud, and telemetry, so they reach real findings faster and with fewer dead ends.
Evaluation: build the evals, benchmarks, and graders that tell us whether an agent actually got better, and make them part of how every change ships.
Model selection and tuning: compare models, prompts, and agent designs on cost, latency, and quality, and turn the results into production decisions.
Model and agent security: defend our agents against prompt injection, data exfiltration, and manipulation by the very systems they test, and research the security of LLM-based applications our customers build.
Reliability at scale: make long-running agents dependable across thousands of runs: verification, self-checks, and sensible stopping.
Learning from the field: study agent runs from customer engagements, find where reasoning broke, and turn each failure into an eval and a fix.
What we're looking for
Hands-on experience building, evaluating, or improving LLM-based agents or systems in production.
A rigorous, empirical approach: you design experiments, distrust single anecdotes, and let the evals decide.
Strong engineering skills: you write production-quality code (Python, TypeScript, or Go) and build tools other people rely on.
A working understanding of security, or a strong drive to learn it fast: how real systems are attacked and how findings are validated.
Familiarity with LLM security risks such as prompt injection, jailbreaks, and tool misuse.
You build with AI coding agents daily (e.g., Claude Code, Cursor) and have opinions about what makes them reliable.
Nice to have
Research background in machine learning, AI safety, or security: publications, open-source work, or talks.
Offensive security experience: penetration testing, red teaming, bug bounty, or CTFs.
Experience with reinforcement learning, fine-tuning, or synthetic data generation for agents.
Experience with graph data models or reasoning over structured data.
Prior early-stage startup experience.
Compensation & benefits
Competitive salary, depending on level and experience.
Early-stage equity: you're joining early; you'll own a real piece of what we build.
Comprehensive medical, dental, and vision coverage, and the equipment you need to do your best work.
Based in San Francisco; we work in person.
Tolmo is building a team with wide-ranging backgrounds, perspectives, and paths into security; we think it makes our product and judgment better. If you're excited about this role but don't match every point above, we'd still like to hear from you. We're an equal opportunity employer and welcome applicants of every background.
See All 262+ AI Research Engineer Jobs in California
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Find AI Research Engineer JobsAI Research Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
AI Research Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- Meta37

- ByteDance26

- TikTok15

- Google14

- Bosch7

Top Industries Hiring
- Technology & Software26
- Science & Research12
- Manufacturing4
- Automotive3
- Artificial Intelligence2
What California Employers Look For
The qualifications that appear most often in AI research engineer jobs across California.
- Master's or PhD in computer science, machine learning, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and training large-scale neural networks or foundation models
- Strong publication record or demonstrated research contributions in a recognized AI subfield
- Ability to collaborate cross-functionally with product, data, and software engineering teams
- Familiarity with distributed computing environments and cloud-based ML infrastructure
AI Research Engineer Jobs in California: Frequently Asked Questions
How do you become a ai research engineer in California?
Most ai research engineers in California enter the field through a graduate degree in computer science, statistics, or a related discipline, typically at the master's or PhD level, from a California research university such as UC Berkeley, Stanford, UCLA, or UC San Diego. California does not require a state-issued license for this role. A strong portfolio of published work, open-source contributions, or internship research at a Bay Area or Southern California lab is the most direct path to a full-time offer.
How much do AI research engineers make in California?
AI research engineers in California earn a median of about $159,100 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $88,920 for the lowest 10% to over $275,320 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai research engineers in California?
Employers hiring ai research engineers in California right now include Meta, ByteDance, and TikTok, based on current listings on Migrate Mate as of November 2026. California's concentration of major tech headquarters, AI-focused startups, and defense research institutions means hiring is spread from the Bay Area down through Los Angeles and San Diego.
Which California cities have the most ai research engineer jobs?
San Jose, San Francisco, and Mountain View have the most ai research engineer openings in California. The Bay Area leads because it hosts the global headquarters of Google, Meta, Apple, and dozens of AI-native startups, while Los Angeles draws from a growing tech and entertainment-AI sector and San Diego benefits from Qualcomm, biotech firms, and defense research contractors that run active machine learning programs.
Are there remote ai research engineer jobs in California?
Yes, and more than most fields. About 44% of ai research engineer openings tied to California are remote or hybrid as of November 2026, reflecting how much of the work involves coding, experimentation, and model evaluation rather than on-site lab access. The most remote-friendly portions of the role tend to be applied research, model fine-tuning, and literature review, while roles requiring specialized compute clusters or collaborative whiteboarding often default to hybrid arrangements.
How can I get hired as a ai research engineer in California with little or no experience?
The most realistic entry path is a research internship or university research assistantship, ideally at a California institution with strong industry ties such as UC Berkeley's BAIR lab, Stanford HAI, or UCLA's Center for Vision, Cognition, Learning and Autonomy. Companies like Google, Meta, and Nvidia run structured research residency and university-grad programs that target candidates without full-time experience. Transitioning from a machine learning engineer, data scientist, or software engineer role at a California employer and gradually shifting toward research projects is another common route, with a strong GitHub portfolio and even one co-authored paper significantly improving your candidacy.
Where can I find and apply to ai research engineer jobs in California?
You can find and apply to ai research engineer jobs in California on Migrate Mate, which lists current California openings updated regularly. Search the listings for roles that match your specialization and experience level, then apply directly to the ones that fit.
See All 262+ AI Research Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find AI Research Engineer Jobs