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Llm 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 ...

Uncountable

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 ...

Near AI

LLM Inference Engineer

OR · On-site +1

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 ...

Near AI

LLM Inference Engineer

San Francisco, CA · On-site +1

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 ...

Digital Links Inc

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.

Xsolla

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 ...

Hexaware Technologies, Inc

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 ...

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 ...

AMSYS Talent

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 ...

EnCharge AI

LLM Inference Deployment Engineer

$180K - $240K/yr

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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How much do llm jobs pay per year?

As of Jul 14, 2026, the average yearly pay for llm in the United States is $142,663.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,000.00 and $157,500.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level positions in artificial intelligence, such as AI research directors, senior machine learning engineers, or AI executives, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact on business or research outcomes.

What are the key skills and qualifications needed to thrive as an LLM (Master of Laws) graduate, and why are they important?

To thrive as an LLM graduate, you need advanced knowledge of legal principles, strong research and analytical skills, and a prior law degree such as an LLB or JD. Familiarity with legal databases, research tools like Westlaw or LexisNexis, and sometimes bar admission or certification in specific jurisdictions is advantageous. Exceptional written and verbal communication, attention to detail, and cross-cultural competence are standout soft skills in this field. These abilities are crucial for interpreting complex legal issues, advising clients, and succeeding in global or specialized legal practice.

What can you do with an LLM degree?

An LLM degree qualifies individuals for advanced legal roles such as legal analyst, compliance officer, or law professor. It provides specialized knowledge in areas like international law, tax law, or human rights, and often requires strong research, writing, and analytical skills. Graduates may work in law firms, government agencies, or corporate legal departments.

What are LLMs (Large Language Models)?

LLMs, or Large Language Models, are advanced artificial intelligence systems designed to understand and generate human-like text based on vast amounts of data. These models, such as OpenAI's GPT series, are trained on diverse datasets and can perform a range of tasks, including answering questions, writing content, translating languages, and more. LLMs work by predicting the next word in a sequence, allowing them to create coherent and contextually relevant responses. They are widely used in applications like chatbots, virtual assistants, and automated content generation.

Does LLM mean lawyer?

In the context of a job title, LLM typically refers to a Master of Laws degree, not a lawyer. An LLM credential can enhance legal expertise but does not automatically qualify someone as a practicing attorney. To become a lawyer, one must pass the bar exam and meet licensing requirements in their jurisdiction.

What jobs can you do with LLM?

With an LLM (Master of Laws), you can pursue careers in legal practice, such as lawyer, legal consultant, or in-house counsel. It also qualifies you for roles in legal research, compliance, policy analysis, and academia, often requiring strong analytical and research skills.

What does LLM mean for AI?

In the context of AI jobs, LLM stands for Large Language Model, which refers to advanced AI systems trained on vast amounts of text data to understand and generate human-like language. Professionals working with LLMs often focus on model training, fine-tuning, and deployment using tools like Python and machine learning frameworks such as TensorFlow or PyTorch.

What Is an LL.M.?

A Master of Laws, or LL.M., is an advanced legal degree designed for lawyers or legal scholars who want to demonstrate their expertise in a specific area of law after law school. While a juris doctoris (JD) is the most common degree people receive at law school, an LL.M. is a secondary degree that typically takes an additional year to complete. The LL.M. curriculum includes coursework in U.S., Canadian, and international law, and is meant for an attorney wanting to specialize in a specific area of law. An LL.M. also provides foreign attorneys with the necessary skills and background to practice law in the United States.

Is ChatGPT an LLM?

ChatGPT is an example of a large language model (LLM) developed by OpenAI. As an LLM, it is trained on vast amounts of text data to generate human-like responses and is used in various AI applications. Working with LLMs as a job may involve skills in machine learning, natural language processing, and programming.

What is the difference between Llm vs Paralegal?

AspectLlmParalegal
Required CredentialsLaw degree (JD or equivalent), possibly an LLM for specializationAssociate's degree or certificate in paralegal studies
Work EnvironmentLaw firms, corporate legal departments, academiaLaw firms, corporate legal departments, government agencies
Industry UsageLegal practice, academia, researchLegal support, case preparation, client communication

The main difference is that an Llm is an advanced law degree for specialization or academic purposes, while a paralegal provides legal support and case assistance without being licensed to practice law. Both roles work closely within legal environments, but the Llm is more focused on legal expertise and research, whereas paralegals handle administrative and preparatory tasks.

What is a LLM in a career?

An LLM in a career context typically refers to a Master of Laws degree, a postgraduate qualification for legal professionals seeking specialization or advanced knowledge in areas such as international law, corporate law, or human rights. It can enhance career prospects, qualify individuals for higher-level positions, or prepare them for academia or legal practice. The degree usually requires completing coursework, research, and a thesis, and may involve passing relevant licensing exams depending on the jurisdiction.

What are some common challenges faced by professionals working with large language models (LLMs) and how can they be addressed?

Professionals working with large language models often encounter challenges such as managing computational resource demands, ensuring data privacy, and mitigating biases in model outputs. Collaboration with data engineers and IT teams is essential to optimize infrastructure and streamline model deployment. Staying updated on best practices and regulatory guidelines helps address ethical concerns and improve model performance. Continuous monitoring and iteration are key to maintaining accuracy and relevance in real-world applications.

What does LLM mean in Masters?

In the context of a master's degree, LLM stands for Master of Laws, a postgraduate academic degree focused on legal studies. It is often pursued by law graduates seeking specialization or advanced knowledge in areas such as international law, corporate law, or human rights. The program typically requires completing coursework and a thesis or research project.
More about Llm jobs
What cities are hiring for Llm jobs? Cities with the most Llm job openings:
What are the most commonly searched types of Llm jobs? The most popular types of Llm jobs are:
What states have the most Llm jobs? States with the most job openings for Llm jobs include:
What job categories do people searching Llm jobs look for? The top searched job categories for Llm jobs are:
Llm jobs near you
Infographic showing various Llm job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $142,663 per year, or $68.6 per hour.
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

Apply