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Llm Project Jobs (NOW HIRING)

Gap International

AI/LLM Engineer

Springfield, PA · On-site

This role offers the opportunity to work on impactful projects, including dialog-driven learning ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

This role offers the opportunity to work on impactful projects, including dialog-driven learning ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

Gap International

AI/LLM Engineer

Philadelphia, PA · On-site

This role offers the opportunity to work on impactful projects, including dialog-driven learning ... As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on ...

Dynamo AI

ML Engineer -- LLM Privacy

San Francisco, CA · On-site

Preferred : • Previous projects or research in LLM privacy. Company : The enterprise platform for enabling private, secure, and regulation-compliant Gen AI models. Founded in 2021, the company is ...

Sierra Nevada Corporation

$108K - $149K/yr

You will take ownership of specific projects, perform data analysis, and optimize models for ... Design, implement, and optimize platform services such as the LLM gateway, model routing, and ...

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Llm Project information

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How much do llm project jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for llm project in the United States is $72.32, according to ZipRecruiter salary data. Most workers in this role earn between $59.62 and $85.34 per hour, depending on experience, location, and employer.

What is an LLM project?

An LLM project typically refers to a research or practical project undertaken as part of a Master of Laws (LLM) degree or, in the context of artificial intelligence, a project involving large language models (LLMs). In law, it involves in-depth study, legal analysis, or research on a specialized topic within the legal field. In AI, an LLM project often includes designing, training, or applying large language models like GPT to solve real-world problems. The specific nature and requirements of an LLM project can vary depending on the academic institution or AI research context.

What are the key skills and qualifications needed to thrive as a Large Language Model (LLM) project manager, and why are they important?

To excel as an LLM Project Manager, you need a solid background in artificial intelligence, project management, and software development, often supported by a degree in computer science or engineering. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems, and agile project management tools is typically required. Strong leadership, communication, and problem-solving skills help manage cross-functional teams and complex project requirements. These competencies ensure effective coordination, timely delivery, and the successful deployment of cutting-edge AI solutions.

What are the common challenges faced when managing an LLM project, and how can they be addressed?

Managing an LLM (Large Language Model) project often involves challenges such as ensuring data privacy, handling large-scale computational resources, and maintaining model accuracy over time. Close collaboration between data scientists, engineers, and project managers is essential to address these issues. It's important to establish clear data governance policies, optimize workflows for model training and deployment, and regularly evaluate model outputs for bias and relevance. Proactively communicating with stakeholders and staying current with industry best practices can help teams navigate these complexities and deliver successful LLM solutions.
Infographic showing various Llm Project job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $150,423 per year, or $72.3 per hour.

Engineering Manager, LLM Performance

Santa Clara, CA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

Full-time

Re-posted 16 days ago

Key responsibilities

  • Lead and grow a team responsible for pushing the performance of LLM inference across multiple LLM frameworks.

  • Drive the design, implementation, and optimization of features that are key to performance in LLM inference.

  • Lead software development execution, with responsibility for project planning, milestone delivery, and cross-functional coordination.

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

At NVIDIA, we aren't just powering the AI revolution-we're accelerating it. We are accelerating LLM inference across the stack and across all open source LLM frameworks like TensorRT LLM, vLLM and SGLang. With demand for AI exploding, particularly in the realm of large language models (LLMs) and vision language models (VLMs, VLAs), we are significantly expanding our team.
We're seeking a highly skilled and driven Engineering Manager to take the lead in accelerating the next generation of LLM/VLM/VLA inference software technologies that will define the future of AI. This is a high-impact, hands-on leadership role at the intersection of deep technical expertise and world-class management. You won't just manage; you'll architect and guide a brilliant team of engineers who are pushing the performance of LLM inference. Your work will be highly collaborative, interfacing directly with NVIDIA Researchers, GPU Architects, and other teams across the company to ensure we ship production-grade, lightning-fast software that sets the global standard for AI performance.
What You'll Be Doing:
  • Lead and grow a team responsible for pushing the performance of LLM inference across multiple LLM frameworks, including TensorRT LLM, vLLM, SGLang and Dynamo on our datacenter products.
  • Drive the design, implementation and optimization of features that are key to performance in LLM inference.
  • Continuously improve the performance of LLM inference on current and upcoming NVIDIA datacenter architectures and GPUs.
  • Continuously improve the performance of LLM inference of important foundation models.
  • Work with inference benchmark teams to help tune performance for key workloads.
  • Integrating cutting-edge technologies developed at NVIDIA and offering an intuitive developer experience for LLM deployment.
  • Lead software development execution, with responsibility for project planning, milestone delivery, and cross-functional coordination.

What We Need to See:
  • MS, PhD, or equivalent experience in Computer Science, Computer Engineering, AI, or a related technical field.
  • 7+ overall years of overall software engineering experience, including 3+ years of technical leadership experience.
  • Proven ability to lead and scale high-performing engineering teams, especially across distributed and cross-functional groups.
  • Strong background in C++ or Python, with expertise in software design and delivering production-quality software libraries.
  • Demonstrated expertise in large language models (LLM) and/or vision language models (VLM) and/or inference in general.

Ways to Stand Out from the Crowd:
  • Deep understanding of GPU architecture, CUDA programming, and system-level performance tuning.
  • Background in LLM inference or working with frameworks such as TensorRT-LLM, vLLM, or SGLang.
  • Passion for building scalable, user-friendly APIs and enabling developers in the AI ecosystem.
  • Have a proven track record of growing and managing a team that encourages idea sharing, empowers team members, and provides opportunities for professional growth.

#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

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Benefits

Hours and flexibility

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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