Llm Engineer Jobs in California
Llm engineer jobs in California sit at the center of one of the most active AI hiring markets in the world, with demand concentrated in foundation model development, retrieval-augmented generation, and enterprise AI deployment at every level from junior engineer to principal. San Francisco, San Jose, and Los Angeles account for the heaviest share of openings, anchored by employers like Google, Meta, and Salesforce, which maintain large California AI research and engineering teams. The most sought-after specializations are fine-tuning and alignment, inference optimization, and LLM-powered application architecture. Find a role that fits below and apply directly.
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INTRODUCTION
We are now looking for a High-Performance LLM Training Engineer! NVIDIA is seeking experienced engineers specializing in performance analysis and optimization to improve the efficiency of LLM training workloads, which are shaping the world's most advanced computing systems. This position focuses on optimizing NVIDIA’s high-performance LLM software stack in frameworks like PyTorch and JAX for high-performance training on thousands of GPUs, while also helping shape hardware roadmaps for the next generation of GPUs powering the AI revolution.
ROLE AND RESPONSIBILITIES
Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.
Understand the big picture of training performance on GPUs, prioritizing and then solving problems across all state-of-the-art neural networks.
Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
Build and support NVIDIA submissions to the MLPerf Training benchmark suite.
Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
Build tools to automate workload analysis, workload optimization, and other critical workflows.
BASIC QUALIFICATIONS
MS in Computer Science, Electrical Engineering or Computer Engineering (or equivalent experience).
Strong background in deep learning and neural networks, in particular training.
A deep background in computer architecture and familiarity with the fundamentals of GPU architecture.
Proven experience analyzing and tuning application performance & processor and system-level performance modeling.
* Programming skills in C++, Python, and CUDA.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 19, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2019451
INTRODUCTION
We are now looking for a High-Performance LLM Training Engineer! NVIDIA is seeking experienced engineers specializing in performance analysis and optimization to improve the efficiency of LLM training workloads, which are shaping the world's most advanced computing systems. This position focuses on optimizing NVIDIA’s high-performance LLM software stack in frameworks like PyTorch and JAX for high-performance training on thousands of GPUs, while also helping shape hardware roadmaps for the next generation of GPUs powering the AI revolution.
ROLE AND RESPONSIBILITIES
Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.
Understand the big picture of training performance on GPUs, prioritizing and then solving problems across all state-of-the-art neural networks.
Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
Build and support NVIDIA submissions to the MLPerf Training benchmark suite.
Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
Build tools to automate workload analysis, workload optimization, and other critical workflows.
BASIC QUALIFICATIONS
MS in Computer Science, Electrical Engineering or Computer Engineering (or equivalent experience).
Strong background in deep learning and neural networks, in particular training.
A deep background in computer architecture and familiarity with the fundamentals of GPU architecture.
Proven experience analyzing and tuning application performance & processor and system-level performance modeling.
* Programming skills in C++, Python, and CUDA.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 19, 2026. This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2019451
See All 29 Llm Engineer Jobs in California
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Find Llm Engineer JobsLlm Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Llm Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- ByteDance5
- Zoox5
- TikTok4
- Microsoft3
- NVIDIA3
Top Industries Hiring
- Technology & Software13
- Artificial Intelligence5
- Automotive5
- Media & Entertainment3
- Social Media3
What California Employers Look For
The qualifications that appear most often in llm engineer jobs across California.
- Bachelor's or master's degree in computer science, AI, or a closely related technical field
- Hands-on experience building or fine-tuning large language models using PyTorch or JAX
- Proficiency in Python and familiarity with transformer architectures such as GPT or LLaMA
- Experience deploying LLM applications via APIs, vector databases, or RAG pipelines
- Ability to evaluate model performance and implement safety, alignment, or RLHF techniques
- Familiarity with cloud infrastructure on AWS, Google Cloud, or Azure for model serving
Llm Engineer Jobs in California: Frequently Asked Questions
How do you become a llm engineer in California?
Most llm engineers in California enter through a computer science, data science, or electrical engineering degree, though a growing number transition from software engineering or ML research roles. No state license is required. California employers, especially in the Bay Area, weight demonstrated project experience heavily, so a portfolio showing fine-tuning experiments, open-source contributions, or published benchmarks often matters as much as formal credentials when applying.
Which companies hire llm engineers in California?
Employers hiring llm engineers in California right now include ByteDance, Zoox, and TikTok, based on current listings on Migrate Mate as of June 2026. California's concentration of AI-native startups and large tech headquarters means openings range from early-stage model research roles to production-scale deployment positions at established platforms.
Which California cities have the most llm engineer jobs?
San Jose, Foster City, and Mountain View have the most llm engineer openings in California. San Francisco and San Jose dominate because of the Bay Area's density of AI labs, foundation model companies, and major tech headquarters, while Los Angeles has expanded rapidly as entertainment and enterprise software firms there invest in generative AI teams.
Are there remote llm engineer jobs in California?
Yes, and more than most fields. About 10% of llm engineer openings tied to California are remote or hybrid as of June 2026, reflecting the desk-based and collaborative-tooling nature of the work. Roles focused on prompt engineering, evaluation pipelines, and API integration tend to be the most remote-friendly, while positions that require access to proprietary GPU clusters or on-site research teams are more likely to require in-person presence.
How can I get hired as a llm engineer in California with little or no experience?
The most realistic entry path is through an ML engineering or software engineering role at a California company that is actively building AI products, then moving into LLM-specific work once inside. Large California employers like Google and Meta run university new-grad programs that place candidates directly onto model and AI teams. Building a visible portfolio on GitHub, contributing to open-source projects like Hugging Face, and completing a recognized ML specialization credential gives candidates without industry experience a concrete edge in California screening processes.
Where can I find and apply to llm engineer jobs in California?
You can find and apply to llm engineer jobs in California on Migrate Mate, which lists current California openings. Search the available roles, find the ones that fit your background and preferences, and apply directly to each position from the listing.
See All 29 Llm Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
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