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Llm 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 ยท 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 ...

Java AI/LLM

Glen Lyn, VA ยท 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

$58.75 - $77.25/hr

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 will be ...

Principal Engineer, LLM

OR ยท On-site +1

As a Principal Engineer - GenAI/LLM, you will provide technical leadership across multiple cross-functional teams, shaping the vision, architecture, and adoption strategy for our new GenAI platform ...

AI LLM Engineer

Atlanta, GA ยท On-site +1

AI / LLM Engineering & Agentic Systems * Design, build, and deploy LLM powered applications using architectures such as Retrieval Augmented Generation (RAG), tool augmented agents, and multi agent ...

Sr Applied LLM Engineer

San Francisco, CA ยท 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 ...

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 ...

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 ...

LLM Engineer

Dallas, TX ยท 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 ...

As a Principal Engineer - GenAI/LLM, you will provide technical leadership across multiple cross-functional teams, shaping the vision, architecture, and adoption strategy for our new GenAI platform ...

LLM Infrastructure Engineer

Houston, TX ยท 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 ...

LLM Engineer

Dallas, TX ยท 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 ...

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How much do llm jobs pay per year?

As of Jun 11, 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 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 is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and programming. These positions usually involve leadership, strategic planning, and extensive experience, and may include stock options or bonuses that contribute to the total compensation package.

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 can also enhance expertise in specialized areas like international law or intellectual property, often requiring strong research, writing, and analytical skills. The degree may lead to opportunities in law firms, corporate legal departments, or government agencies.

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.

What jobs can you do with LLM?

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

What job makes $10,000 a month without a degree?

A machine learning engineer or AI specialist can earn $10,000 or more per month through expertise in developing and deploying AI models, often requiring strong programming skills in Python and knowledge of frameworks like TensorFlow or PyTorch. Success in such roles depends on experience, project complexity, and the ability to work independently or in high-demand environments, often without formal degrees but with relevant skills and certifications.

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.

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 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 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:
LLM Engineer

LLM Engineer

Luminary Cloud

San Mateo, CA โ€ข On-site

Full-time

Posted 7 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