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Assistant Llm Developer Jobs in California (NOW HIRING)

The Role We're looking for an LLM Engineer to architect our Physics AI Copilot-the next generation of intelligent assistants for engineering workflows. You'll work at the intersection of large ...

AI/LLM Integration Engineer

San Diego, CA

$110K - $148K/yr

As our AI/LLM engineer, you won't just write prompts -- you'll define how the system thinks. You'll ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Data Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Experience building AI agents, LLM-powered applications, or tool-using assistants that integrate ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

Data Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Experience building AI agents, LLM-powered applications, or tool-using assistants that integrate ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

Experience building AI agents, LLM-powered applications, or tool-using assistants that integrate ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

... language models to assist technicians in troubleshooting complex industrial issues ... LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

The role involves developing intelligent tools to assist technicians in troubleshooting complex ... LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

... assistants to support technicians in diagnosing and resolving anomalies or failures in factory ... LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques ...

Technical Product Manager, LLM/ML Domain

San Jose, CA · On-site

$195K - $226K/yr

... engineering to level up Agoda's platforms to be more compatible with AI coding assistants and ... with ML Ops and/or LLM Ops concepts (model lifecycle, evaluation, monitoring, versioning ...

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Assistant Llm Developer information

What is the difference between Assistant Llm Developer vs Machine Learning Engineer?

AspectAssistant Llm DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; familiarity with NLP and LLMsBachelor's or higher in CS, Data Science, or related; strong ML background
Work EnvironmentTech companies, AI startups, research labsTech firms, AI companies, research institutions
Employer & Industry UsageFocus on developing and fine-tuning language modelsDesigning, building, deploying ML models across domains

Assistant Llm Developers typically focus on developing and fine-tuning language models, often working closely with NLP teams. Machine Learning Engineers have a broader scope, designing and deploying various ML models across industries. Both roles require strong technical skills, but Assistant Llm Developers specialize more in language-specific AI applications.

What are the most commonly searched types of Llm Developer jobs in California? The most popular types of Llm Developer jobs in California are:
LLM Engineer

LLM Engineer

Luminary Cloud

San Mateo, CA • On-site

Full-time

Re-posted 15 days ago


Job description

Luminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.
About Luminary
Luminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.
The Role
We're looking for an LLM Engineer to architect our Physics AI Copilot-the next generation of intelligent assistants for engineering workflows. You'll work at the intersection of large language models and domain-specific engineering challenges, creating AI experiences that dramatically accelerate how engineers work.
Responsibilities
  • Develop Agentic AI systems: Design and implement tools for agents to call; build reasoning, planning, and orchestration capabilities that enable the copilot to autonomously execute complex engineering workflows

  • Design and optimize RAG pipelines: Build retrieval-augmented generation systems over engineering documentation, physics simulation results, and domain knowledge bases

  • Implement memory and context management: Create persistent conversation memory and context systems that maintain coherent, long-running engineering sessions

  • Fine-tune and adapt LLMs: Customize foundation models for Physics AI and physics simulation domain expertise through fine-tuning, prompt engineering, and evaluation frameworks

  • Deploy and scale LLM infrastructure: Build robust, production-grade systems for self-hosting and serving LLMs, optimizing for latency, cost, and reliability

  • Integrate with Physics AI and physics simulation platform: Connect LLM capabilities with Luminary's Physics AI training/evaluation/inference pipelines, physics simulation solvers, mesh tools, and analytics APIs to enable end-to-end automation

  • Establish evaluation frameworks: Define metrics and build testing infrastructure to measure copilot quality, accuracy, and user satisfaction

  • Collaborate cross-functionally: Work closely with Physics AI researchers, platform engineers, and product teams to deliver customer-centric AI experiences

Qualifications
Required
  • Bachelor's degree or higher in Computer Science, Mechanical Engineering, Aerospace Engineering, or related field
  • 5+ years of experience building production software or ML systems
  • 2+ years of hands-on experience developing LLM-powered applications
  • Strong proficiency in Python
  • Proficiency using coding agents such as Claude Code
  • Experience with Agent Evals
  • Deep understanding of LLM architectures, prompting techniques, and their capabilities/limitations
  • Experience designing tools/functions for agents to call, with planning and reasoning
  • Experience with multi-agent orchestration and coordination
  • Hands-on experience with RAG systems and memory/context management, including vector databases, embedding models, chunking strategies, and long-running session handling
  • Experience building MCP (Model Context Protocol) servers to expose tools and capabilities to external agents
  • Experience with agent frameworks (e.g., LangChain, LlamaIndex, Google ADK, Autogen, Claude Agent SDK, or custom solutions)
  • Familiarity with Physics AI, CAE, or physics simulation domains a plus
  • Experience fine-tuning LLMs for domain-specific applications
  • Hands-on experience self-hosting and serving LLMs in production environments

Nice to Have
  • Experience with TypeScript for full-stack development
  • Experience with Go for backend systems
  • Familiarity with Kubernetes for container orchestration and deployment
  • Experience with GPU infrastructure and optimization for LLM inference
  • Experience deploying ML systems on cloud platforms (GCP, AWS, Azure) or on-prem infrastructure
  • Background in CFD, structural analysis, or thermal simulation
  • Experience building developer tools or copilot-style products
  • Contributions to open-source LLM projects or research publications