▷ 15h Left: GPU Optimization Engineer

11 hours ago


Delhi, India BitOoda Full time
Job Posting: GPU Optimization Engineer (Bare Metal Expertise)

Location: Remote

Job Type: Full-Time

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.- Work with a talented and collaborative team of engineers.- Opportunities to work on cutting-edge GPU and HPC projects.- A flexible and dynamic startup environment where you can grow and innovate.

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