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Remote Nvidia Research Jobs (NOW HIRING)

Weekday AI

CUDA Engineering Expert

$80 - $100/hr

At least 1 year of professional or graduate-level research experience working with GPUs * Strong ... Experience optimizing kernels for NVIDIA Blackwell hardware is a plus * Familiarity with NSight ...

PICTOR LABS INC

$89K - $123K/yr

This innovation supports the critical evolution from research applications to clinical deployment ... Remote US Company: Pictor Labs Employment Type: Full-time Responsibilities * Design, development ...

Centific

Speech Research Intern-2

$45/hr

Distributed training/serving (FSDP/DeepSpeed), and experience with ESPnet, SpeechBrain, or NVIDIA ... Redmond(Preferred) or Remote * Duration: What We Offer * Competitive stipend and hands-on projects ...

Centific

Speech Research Intern-2

$45/hr

Distributed training/serving (FSDP/DeepSpeed), and experience with ESPnet, SpeechBrain, or NVIDIA ... Redmond(Preferred) or Remote * Duration: What We Offer * Competitive stipend and hands-on projects ...

Quantiphi, Inc.

Architect ML - AI Researcher

$65.25 - $84/hr

USA - Remote Role Overview: As an ATA Machine Learning Engineer in healthcare, you'll deliver multi ... research, experimentation, data management, and model evaluation. * Develop high-level solution ...

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$37K

$106K

$142.5K

How much do remote nvidia research jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote nvidia research in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Nvidia Research vs Remote Nvidia Data Scientist?

AspectRemote Nvidia ResearchRemote Nvidia Data Scientist
Required CredentialsAdvanced degrees in Computer Science, AI, or related fields; research publicationsDegree in Data Science, Statistics, or related; strong programming skills
Work EnvironmentResearch labs, collaborative projects, experimental workData analysis, modeling, and deployment in business settings
Employer & Industry UsageNvidia's R&D divisions, academic collaborationsNvidia's analytics teams, product development

Remote Nvidia Research focuses on innovative AI and machine learning research, often involving experimental projects and publications. In contrast, Remote Nvidia Data Scientists analyze data to inform business decisions and develop models. Both roles require technical expertise but differ in their primary objectives and work environment.

More about Remote Nvidia Research jobs
What cities are hiring for Remote Nvidia Research jobs? Cities with the most Remote Nvidia Research job openings:
What are the most commonly searched types of Nvidia Research jobs? The most popular types of Nvidia Research jobs are:
What states have the most Remote Nvidia Research jobs? States with the most job openings for Remote Nvidia Research jobs include:
What job categories do people searching Remote Nvidia Research jobs look for? The top searched job categories for Remote Nvidia Research jobs are:
Remote Nvidia Research jobs near you
Infographic showing various Remote Nvidia Research job openings in the United States as of July 2026, with employment types broken down into 4% Locum Tenens, 10% As Needed, 78% Full Time, 1% Part Time, 1% Contract, and 6% Nights. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution, with an average salary of $106,012 per year, or $51 per hour.

CUDA Engineering Expert

Weekday AI

Remote

$80 - $100/hr

Part-time

Re-posted 13 days ago

Job description

This role is for one of our clients
Compensation: $80-$100 per hourWe are seeking GPU kernel optimization experts to contribute to a project with a leading AI lab. This opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis. You'll help evaluate, optimize, and reason about GPU kernels across modern hardware environments. This is a contract-based opportunity for specialists who enjoy squeezing performance out of modern GPU architectures.
Requirements
Key Responsibilities
  • Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization
  • Use profiler metrics such as L2 cache hit rate, L2 throughput, occupancy, and related signals to guide kernel improvements
  • Review GPU kernel implementations and identify bottlenecks without requiring extensive background in the underlying algorithms
  • Write, modify, and reason about C++17, Python, and GPU programming code
  • Apply CUDA, HIP, shader programming, or related kernel programming expertise to improve performance outcomes
  • Document optimization decisions clearly, including when specific profiler metrics are or are not useful
Ideal Qualifications
  • Available to work at least 20 hrs/wk
  • Fluent in core C++ features through C++17
  • Working knowledge of Python and Git
  • Fluent in at least one GPU programming model, such as CUDA, HIP, Slang, HLSL, GLSL, or related kernel programming
  • At least 1 year of professional or graduate-level research experience working with GPUs
  • Strong understanding of GPU profiler performance metrics and how to use them to optimize kernels
  • Ability to optimize GPU kernels without needing deep prior context on every algorithm
  • Experience with CUDA, HIP, CUDA C++ Core Libraries, inline PTX assembly, or tensor core-level optimization is a plus
  • Experience optimizing kernels for NVIDIA Blackwell hardware is a plus
  • Familiarity with NSight Compute is a plus
  • Prior experience with GPU hardware organizations such as NVIDIA, AMD, or Qualcomm is a plus
  • Open-source contributions related to GPU kernel optimization are a plus
4. Application Process
  • Submit your resume or relevant technical background to get started
  • Qualified applicants may be asked to complete a brief technical assessment or submit additional information

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Contract and Payment Terms
  • You will be engaged as an independent contractor.
  • This is a fully remote role that can be completed on your own schedule.
  • Projects can be extended, shortened, or concluded early depending on needs and performance.
  • Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
  • Payments are weekly on Stripe or Wise based on services rendered.
  • Please note: We are unable to support H1-B or STEM OPT candidates at this time.

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