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Freelance Nvidia Deep Learning Jobs (NOW HIRING)

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX

$103K - $142K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and ...

Nvidia

Solutions Architect, Industry Accounts

Santa Clara, CA · On-site

$74 - $97.50/hr

Collaborating deeply with NVIDIA deep learning engineers, SDK product and framework teams, Deep Learning Institute (DLI), and NV Research to ensure developer enablement materials are best-in-class ...

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and ...

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Freelance Nvidia Deep Learning information

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How much do freelance nvidia deep learning jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for freelance nvidia deep learning in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is the difference between Freelance Nvidia Deep Learning vs Freelance Machine Learning Engineer?

AspectFreelance Nvidia Deep LearningFreelance Machine Learning Engineer
Required CredentialsKnowledge of Nvidia frameworks, CUDA, deep learning modelsBroader ML skills, Python, frameworks like TensorFlow or PyTorch
Work EnvironmentProject-based, remote, often with tech companies or startupsSimilar, project-based or consulting roles in various industries
Industry UsagePrimarily tech, AI, and research sectors using Nvidia hardwareWide industry application including finance, healthcare, and tech

Freelance Nvidia Deep Learning specialists focus on Nvidia-specific tools and deep learning models, often working on AI projects utilizing Nvidia hardware. Freelance Machine Learning Engineers have a broader scope, working with various ML frameworks and industries. Both roles are project-based and often remote, but Nvidia Deep Learning roles require specialized knowledge of Nvidia technologies.

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What cities are hiring for Freelance Nvidia Deep Learning jobs? Cities with the most Freelance Nvidia Deep Learning job openings:
What are the most commonly searched types of Nvidia Deep Learning jobs? The most popular types of Nvidia Deep Learning jobs are:
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Freelance Nvidia Deep Learning jobs near you
Infographic showing various Freelance Nvidia Deep Learning job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Senior Performance Engineer - Deep Learning

Senior Performance Engineer - Deep Learning

NVIDIA

Santa Clara, CA • On-site

Full-time

Re-posted 8 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

Job Summary:
NVIDIA is a leading company in AI technology, and they are seeking a Senior Performance Engineer to enhance their Deep Learning performance engineering team. The role involves building and optimizing libraries and tools for Deep Learning applications, collaborating on systems research, and engaging with the open-source community.
Responsibilities:
• Build and support Transformer Engine, the open-source library for accelerating the training of Large Language Models.
• Collaborate on systems research that improves Deep Learning model performance, such as training using extremely low precision, parallelism methods, etc.
• Implement, benchmark, and optimize new Deep Learning models such as LLMs straight out of groundbreaking research to scale efficiently on NVIDIA GPUs and systems.
• Build and contribute to NVIDIA submissions on community benchmarks such as MLPerf.
• Engage with the open-source community as well as support enterprise customers and partners by delivering the benefits of NVIDIA’s latest hardware and software innovations.
• Influence the design of new hardware generations and core platform software components for NVIDIA hardware and systems.
Qualifications:
Required:
• BS or equivalent experience in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in C++ and Python programming.
• Strong background, experience, or coursework in parallel systems programming, preferably on GPUs.
• Knowledge of Computer Architecture, Code Optimization, and/or Operating Systems.
• Proven experience in developing large software projects.
• Excellent verbal and written communication skills.
Preferred:
• Experience in PyTorch, JAX, or any other DL framework.
• Experience with performance analysis, profiling, and code optimization techniques, especially with multi-GPU or multi-node systems.
• Knowledge of modern LLM architectures, attention mechanisms, and/or low-level DL libraries such as cuBLAS, cuDNN, and cuSOLVER.
• Experience in writing GPU kernels using any of - CUDA, OpenAI Triton, CuTeDSL, Pallas, or other similar libraries.
• Any past contributions to the open source community and/or experience working with multidisciplinary teams also showcase readiness for the team's responsibilities.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

Year founded

1993

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