
GPU Performance Engineer
Adaptive ML
full-time
Posted on:
Location Type: Hybrid
Location: New York City • New York • United States
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About the role
- Build and maintain fast and robust GPU code, focusing on delivering performance improvements in real world applications;
- Write high-quality software in CUDA, CUTLASS, or Triton with a focus on performance and robustness;
- Profile dedicated GPU kernels, optimizing across latency/compute-bound regimes for complex workloads;
- Contribute to our product roadmap, by identifying promising trends that can improve performance;
- Report clearly on your work to a distributed collaborative team, with a bias for asynchronous written communication.
Requirements
- A M.Sc. /Ph.D. in computer science, or demonstrated experience in software engineering, preferably with a focus on GPU-optimization;
- Strong programming skills, preferably with a focus on systems and general purpose GPU programming;
- A track record of writing high performance kernels, having preferably demonstrated ability to reach state of the art performance on well defined tasks;
- Contributions to relevant open-source projects, such as CUTLASS, Triton and MLIR;
- Passionate about the future of generative AI, and eager to build foundational technology to help machines deliver more singular experiences.
Benefits
- Comprehensive medical (health, dental, and vision) insurance;
- 401(k) plan with 4% matching (or equivalent);
- Unlimited PTO — we strongly encourage at least 5 weeks each year;
- Mental health, wellness, and personal development stipends;
- Visa sponsorship if you wish to relocate to New York or Paris.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
CUDACUTLASSTritonGPU programmingperformance optimizationkernel developmentlatency optimizationcompute-bound optimizationsoftware engineeringgenerative AI
Soft Skills
communicationcollaborationreportingasynchronous communicationtrend identification
Certifications
M.Sc.Ph.D.