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Llm Jobs Jobs (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 ...

LLM Applications Engineer

New York, NY · On-site

$130K - $175K/yr

As an LLM Applications Engineer, you will be the architect of our LLM infrastructure. You won't just be building interfaces; you will be designing the retrieval systems, agentic workflows, and data ...

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served. What You ...

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served. What You ...

Java AI/LLM

Glen Lyn, VA · Remote

$52.25 - $67.50/hr

AI/LLM skill with * AI/LLM - hugging face model, OLAMA, LLAMA, Mistral * Agentic AI, Open AI, Gemini * Fine tuning of LLM * Lang chain, Lang flow, FAISS, vector database, Cosine similarity search.

LLM Solutions Architect

Concord, NC · On-site

$85K - $120K/yr

ABOUT YOU We are looking for an LLM Solutions Architect who is a builder at heart -- someone who shapes strategy and ships real systems -- to join our Monetization Products team. The best candidate ...

Python LLM Developer

Irving, TX · On-site

$48.25 - $66.50/hr

Role Python LLM Developer Location: Irving, TX ( day1 onsite, hybrid ) Python LLM Python LLM: Should have very strong in-depth knowledge in Python Programming Programming Fundamentals: Proficiency in ...

Sr Applied LLM Engineer

San Francisco, CA · On-site

$180K - $200K/yr

Sr. Applied LLM Engineer Qualifications * Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience) * 3+ years of software development ...

LLM Infrastructure Engineer

Houston, TX · On-site

$97K - $127K/yr

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance ...

About the Role EnCharge AI is seeking an LLM Inference Deployment Engineer to optimize, deploy, and scale large language models (LLMs) for high-performance inference on its energy efficient AI ...

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Llm Jobs information

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LLM Engineer

LLM Engineer

Luminary Cloud

San Mateo, CA • On-site

Full-time

Re-posted 10 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