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Python Llm Jobs in Nevada (NOW HIRING)

LangChain, Inc

Deployed Engineer (Las Vegas)

Las Vegas, NV · On-site

$155K - $360K/yr

Strong Python, JavaScript and systems fundamentals * Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling

2K Vegas

Lead Software Engineer - Automation

Las Vegas, NV · On-site

$97K - $128K/yr

Tools R&D - Research and apply LLM-based tooling to accelerate development and automation workflows ... Python, Bash, etc). * CI/CD Integration - Deep experience managing and scaling CI/CD systems (e.g ...

Deloitte

CyberArk Senior Consultant

Las Vegas, NV · On-site

Experience with object-oriented programming using languages such as Java, Python, or JavaScript ... Hands-on experience building and deploying GenAI/LLM-powered solutions in client or production ...

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Python, PyTorch, TensorFlow, JAX * LangChain, semantic search, vector embeddings * Prompt engineering & LLM orchestration frameworks * Excellent communication, problem-solving, and project management ...

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Python Llm information

What is a Python LLM job?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

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

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM Engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.

What are the most commonly searched types of Python Llm jobs in Nevada? The most popular types of Python Llm jobs in Nevada are:
What are popular job titles related to Python Llm jobs in Nevada? For Python Llm jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Python Llm jobs in Nevada look for? The top searched job categories for Python Llm jobs in Nevada are:
What cities in Nevada are hiring for Python Llm jobs? Cities in Nevada with the most Python Llm job openings:
Python Llm jobs near you

Deployed Engineer (Las Vegas)

LangChain, Inc

Las Vegas, NV • On-site

$155K - $360K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago

Job description

About Us
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we're at a stage where we're continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
About the Team
The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
About the Role
The Deployed Engineer...You'll work on some of the hardest problems in applied AI - not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
What You'll Do
  • Co-architect and co-build production AI agents with customer engineering teams
  • Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
  • Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
  • Advise customers post-sale on architecture, best practices, and roadmap-level decisions
  • Run technical demos, trainings, and workshops for developer audiences
  • Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
  • Occasionally contribute code upstream when it meaningfully improves customer outcomes
  • This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement

What You'll Bring
  • 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
  • Strong Python, JavaScript and systems fundamentals
  • Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
  • Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
  • Can explain technical tradeoffs clearly and build trust with developer audiences
  • Take responsibility for outcomes, not just recommendations
  • Have a bias toward action and enjoy figuring things out as you go
  • Are excited about operating AI agents in production, not just building demos

Nice to Have's:
  • You've deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
  • Worked with LLM evaluation, observability, or guardrails
  • Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
  • Have shipped and operated production software and are comfortable owning systems under real-world constraints

Compensation
Annual OTE range: $155,000-$360,000 USD
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
Benefits
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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