CUDA Engineer - Kernel Optimization
Mercor · Mumbai Metropolitan Region
- Experience1–2 yrs
- SalaryDisclosed
- Work moderemote
- Posted24 Sept 2026
About Mercor
Mercor is hiring in Mumbai Metropolitan Region in technology software. This role looks for around 1+ years of experience.
Skills
- CUDA
- C++17
- Python
- Git
- HIP
- GPU profiler performance metrics
The role
A GPU kernel optimization engineer at an AI research talent marketplace analyzes and optimizes CUDA kernels using C++17, Python, and GPU profiler metrics, applying HIP and shader programming to improve hardware performance. The role also uses Git and NSight Compute to diagnose bottlenecks and guide efficient kernel improvements.
Full job description
About The Job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: CUDA Engineering Expert
Type: Contract
Compensation: $300 per task
Location: Remote
Role Responsibilities
Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization.Use profiler metrics like L2 cache hit rate and occupancy to guide kernel improvements.Review GPU kernel implementations and identify bottlenecks without deep algorithmic background.Write and modify C++17, Python, and GPU programming code.Apply expertise in CUDA, HIP, and shader programming to improve performance.Document optimization decisions clearly, focusing on profiler metrics' utility.
Qualifications
Must-Have
Available to work at least 20 hrs/wk.Fluent in core C++ features through C++17.Working knowledge of Python and Git.Fluent in one GPU programming model like CUDA or HIP.1+ year of professional or research experience with GPUs.Strong understanding of GPU profiler performance metrics.
Preferred
Experience with CUDA, HIP, and CUDA C++ Core Libraries.Experience optimizing kernels for NVIDIA Blackwell hardware.Familiarity with NSight Compute.Prior experience with NVIDIA, AMD, or Qualcomm.Open-source contributions related to GPU kernel optimization.
Application Process (Takes 20–30 mins to complete)
Submit your resume or relevant technical background.Qualified applicants may complete a brief technical assessment or submit additional information.
Resources & Support
For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcomeFor any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.