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Llm Engineer Jobs (NOW HIRING)

Luminary Cloud

LLM Engineer

San Mateo, CA · On-site

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 ...

First Soft Solutions

LLM Engineer

Dallas, TX · On-site

LLM Engineer Location: Dallas, TX (Onsite) Start: Immediate Role Overview We are looking for a Senior Full Stack AI Engineer with strong experience in building scalable applications and integrating ...

First Soft Solutions

LLM Engineer

Dallas, TX · On-site

LLM Engineer Location: Dallas, TX (Onsite) Start: Immediate Role Overview We are looking for a Senior Full Stack AI Engineer with strong experience in building scalable applications and integrating ...

SmartIPlace

LLM Engineer[Onsite]

Houston, TX · Remote

$170K/yr

LLM Engineer 6-month contract Houston,TX (Onsite) USC/GC Required Skills & Experience -3+ years of large language modeling experience -5+ years of python experience -Strong problem solving skills and ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

They are seeking an AI/LLM Engineer to design and implement advanced AI systems centered on large language models, collaborating with teams to integrate AI capabilities into internal tools and ...

Diablo Convoy

LLM Engineer

Houston, TX · On-site

$120K - $130K/yr

We are seeking a detail-oriented LLM Automation Engineer to support AI-driven data analysis, document processing, automation workflows, and reporting initiatives. This role focuses on using ...

Diablo Convoy

LLM Engineer

Houston, TX · On-site

$120K - $130K/yr

We are seeking a detail-oriented LLM Automation Engineer to support AI-driven data analysis, document processing, automation workflows, and reporting initiatives. This role focuses on using ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

The AI/LLM Engineer will lead the design and implementation of advanced systems centered on large language models, collaborating closely with teams to integrate AI capabilities into internal tools ...

Simple Solutions

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 ...

Gap International

AI/LLM Engineer

Philadelphia, PA

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as ...

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How much do llm engineer jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for llm engineer in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.

What does an LLM Engineer do?

An LLM Engineer designs, develops, and optimizes applications that leverage large language models (LLMs). They fine-tune models, integrate them into products, and improve performance through prompt engineering and model customization. This role requires expertise in machine learning, natural language processing (NLP), and software development. LLM Engineers work closely with data scientists and developers to create AI-driven solutions for various applications such as chatbots, content generation, and code assistance.

What are the main responsibilities of an LLM Engineer on a typical project?

An LLM Engineer is typically responsible for designing, fine-tuning, and deploying large language models to solve specific business or research problems. You will collaborate closely with data scientists, product managers, and software engineers to understand requirements, select the appropriate model architectures, and integrate LLMs into production systems. Routine tasks may include data preprocessing, hyperparameter tuning, model evaluation, and monitoring model performance post-deployment. The role also often involves staying current with rapidly evolving NLP advancements to recommend and implement state-of-the-art solutions.

What are the key skills and qualifications needed to thrive in the Llm Engineer position, and why are they important?

To thrive as an LLM Engineer, you need strong expertise in machine learning, natural language processing, and proficiency with Python, along with a solid understanding of transformer-based models and deep learning frameworks like PyTorch or TensorFlow. Familiarity with cloud platforms, version control systems (e.g., Git), and tools such as Hugging Face Transformers is typically required, and certifications in AI or data science can be advantageous. Excellent problem-solving, collaboration, and communication skills help you work effectively with interdisciplinary teams and present complex findings clearly. These skills enable you to develop, fine-tune, and deploy large language models efficiently in real-world applications.

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Llm Engineer jobs near you
Infographic showing various Llm Engineer job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 92% Full Time, 1% Part Time, 3% Contract, and 3% Nights. Highlights an 76% Physical, 5% Hybrid, and 19% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.
LLM Engineer

LLM Engineer

Luminary Cloud

San Mateo, CA • On-site

Full-time

Posted 2 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

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