GPU Optimization Engineer

3 weeks ago

india BitOoda Full time
Experience Level: Senior

About Us:

We are an innovative company at the forefront of high-performance computing (HPC) and AI, building cutting-edge solutions powered by GPUs and specialized accelerators. We’re looking for a highly skilled GPU Optimization Engineer to design, develop, and optimize software running directly on bare-metal systems, leveraging the full potential of NVIDIA GPUs, AMD GPUs, and other accelerators.

Responsibilities:

- Architect, develop, and optimize high-performance software for GPU-accelerated systems.- Design and implement software that directly interacts with GPU hardware, including NVIDIA CUDA, AMD ROCm, or OpenCL.- Optimize existing ML/DL frameworks (e.g., PyTorch, TensorFlow) for maximum performance on NVIDIA and AMD GPUs.- Work with heterogeneous systems, integrating specialized accelerators like AMD GPUs or custom chips (e.g., SambaNova, Cerebras).- Conduct profiling and tuning to maximize GPU utilization, minimize bottlenecks, and achieve peak system performance.- Collaborate with hardware engineers to exploit features like NVLink, NVSwitch, and RDMA for seamless GPU interconnectivity.- Develop scalable compute pipelines and contribute to performance benchmarking.

Requirements:

- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).- Experience: 5+ years in GPU-accelerated software development, HPC, or related domains.

Technical Skills:

- GPU Programming:- Proficiency in CUDA for NVIDIA GPUs.- Experience with AMD ROCm, HIP, or OpenCL for AMD GPUs.- Frameworks:- In-depth knowledge of PyTorch or TensorFlow with GPU optimization.- Familiarity with ONNX and hardware-agnostic ML frameworks.- Languages:- Proficient in Python, C++, and/or C for performance-critical applications.- Profiling & Optimization:- Hands-on experience with GPU profilers such as NVIDIA Nsight, nvprof, and rocprof.- Ability to identify and mitigate bottlenecks in GPU pipelines.- System Knowledge:- Strong understanding of bare-metal systems, GPU drivers, and OS-level configuration.- Experience with containerized GPU environments (NVIDIA Docker, AMD ROCm containers).

Preferred Skills:

- Experience with multiple accelerator platforms, such as SambaNova or Graphcore.- Familiarity with distributed computing and interconnects like NVLink, InfiniBand, or PCIe.- Knowledge of compiler optimization (LLVM, TVM, XLA).- Familiarity with Kubernetes for GPU cluster management.

What We Offer:

- Competitive salary and benefits package.- Opportunity to work on cutting-edge HPC and AI systems.- Collaborative and innovative work environment with talented engineers.- Flexible work arrangements (remote or hybrid options).

Join us and help redefine the limits of GPU computing

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