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Hourly Large Language Model Llm Jobs (NOW HIRING)

This role focuses on engineering production-ready machine learning applications, Large Language Model (LLM) solutions, and cloud-native ML platforms while partnering closely with Data Science teams ...

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 ...

Founded by Harvard-trained physicians with a vision of offering patient-first care beyond the hospital settings, we've grown into the nation's largest network of outpatient vein, fibroid, vascular ...

The LLM Engineer serves as the organization's AI technical lead responsible for designing, implementing, and optimizing Large Language Model (LLM) solutions that automate business processes, improve ...

LLM Engineer

Northbrook, IL · On-site

$85K - $115K/yr

The LLM Engineer serves as the organization's AI technical lead responsible for designing, implementing, and optimizing Large Language Model (LLM) solutions that automate business processes, improve ...

This role requires expertise in building and deploying Large Language Model (LLM)-powered, production-grade systems within regulated enterprise environments. You will be responsible for end-to-end ...

AI Architect

OR · Remote

Artificial and Large Language Model Architect As an AI & LLM Architect , you will play a pivotal role in designing and implementing the technology architecture for advanced AI (including Large ...

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Hourly Large Language Model Llm information

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How much do hourly large language model llm jobs pay per hour?

As of Aug 4, 2026, the average hourly pay for hourly large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.

What is the difference between Hourly Large Language Model Llm vs Data Scientist?

AspectHourly Large Language Model LlmData Scientist
Required CredentialsKnowledge of AI, NLP, programming skillsDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, AI research labs, freelance projectsCorporate, consulting firms, research institutions
Industry UsageDeveloping and fine-tuning language models, AI applicationsData analysis, predictive modeling, data visualization

While both roles involve working with data and advanced technology, Hourly Large Language Model Llm focuses on developing and deploying AI language models, whereas Data Scientists analyze data to inform business decisions. The roles share skills in programming and data handling but differ in their primary objectives and work environments.

What are the key skills and qualifications needed to thrive as a large language model (LLM) engineer?

To thrive as a Large Language Model (LLM) Engineer, you need a solid background in machine learning, natural language processing, and programming—typically with a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with cloud platforms, and knowledge of model deployment tools are highly valued, along with certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication help you collaborate with cross-functional teams and innovate solutions. These competencies are crucial for developing, optimizing, and scaling LLMs to meet evolving business and research needs.

What are some common challenges faced by hourly large language model (LLM) annotators and how can they be addressed?

Hourly LLM annotators often face challenges such as maintaining consistency in labeling, handling ambiguous or unclear data, and managing the repetitive nature of annotation tasks. To address these challenges, it's helpful to regularly review annotation guidelines, participate in team discussions to clarify uncertainties, and leverage available feedback from quality assurance checks. Collaborating with teammates and project managers can also provide support and ensure alignment on task expectations, making the work environment more collaborative and improving overall accuracy.

What is an hourly large language model LLM?

Hourly Large Language Model (LLM) jobs are roles where individuals work with LLMs, such as ChatGPT or similar AI systems, on an hourly basis. These positions often involve tasks like data annotation, prompt engineering, AI model evaluation, or content generation. Workers may be responsible for improving AI responses, testing models, or creating training data. The 'hourly' aspect means they are paid based on the number of hours worked, rather than a fixed salary or per-project rate. Such jobs are common in tech companies, research organizations, or freelance platforms.
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What cities are hiring for Hourly Large Language Model Llm jobs? Cities with the most Hourly Large Language Model Llm job openings:
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What job categories do people searching Hourly Large Language Model Llm jobs look for? The top searched job categories for Hourly Large Language Model Llm jobs are:
Infographic showing various Hourly Large Language Model Llm job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 47% Full Time, 48% Part Time, 1% Temporary, and 3% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

Manager, Large Language Model Inference

Nvidia

Santa Clara, CA • Hybrid

Full-time

Re-posted 6 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 241 rated software companies


Job description

At NVIDIA, we aren't just powering the AI revolution-we're accelerating it. The TensorRT inference platform is the backbone of modern AI, delivering the industry's fastest and most efficient deployment of cutting-edge deep learning models on every NVIDIA GPU. 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 developing 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 building the core LLM inference runtime. 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 specialized kernel development, runtime optimizations, and frameworks for LLM inference.

  • Drive the design, development, and delivery of production inference software, targeting NVIDIA's next-generation enterprise and edge hardware platforms.

  • 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).

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.

We are widely considered to be one of the technology world's most desirable employers, and we have some of the most forward-thinking and hardworking people in the world working with us. Due to outstanding growth, our best-in-class teams are rapidly growing. If you're a creative self-starter with a real passion for technology, then come join us.

#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 184,000 USD - 287,500 USD for Level 2, and 224,000 USD - 356,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 26, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

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

Year founded

1993