What You’ll Do
- Design and optimize GPU system configurations for AI training and inference
- Analyze performance bottlenecks across compute, memory, networking, and storage
- Work on GPU scheduling, placement, and utilization strategies
- Tune systems for high-density and multi-tenant GPU environments
- Build tools for profiling, benchmarking, and monitoring GPU workloads
- Collaborate with research, platform, and infrastructure teams
- Support deployment and optimization of GPU clusters in production
- Document system behavior and best practices for internal and customer use
You’ll Thrive Here if You
- Have 5+ years of experience in systems engineering or performance optimization
- Possess a strong understanding of GPU architectures and accelerators
- Have experience with Linux systems and low-level performance tuning
- Are comfortable working close to hardware and infrastructure layers
- Demonstrate strong problem-solving and analytical skills
Bonus Qualifications
- Experience with CUDA, ROCm, or GPU kernel optimization
- Familiarity with NCCL, RDMA, or high-speed interconnects
- Experience with AI workloads and frameworks
- Background in high-performance computing environments
Why This Role is Unique
You will directly influence how GPU resources are configured and utilized at scale, improving performance, efficiency, and cost across next-generation AI infrastructure.
Details
- Competitive salary and equity based on experience and skill set
- Flexible work environment
- Applicants must be authorized to work in their respective location
