3 months ago
Base Salary
$190k - $250k/yr
Responsibilities
- Maintain, update, and optimize JAX, PyTorch, CUDA, and ROCm across multiple environments and hardware configurations.
- Own and improve the ML software stack from low-level ROCm/CUDA drivers to high-level training and serving tools.
- Optimize model sharding, partitioning, distributed training, and distributed serving across multi-node GPU and accelerator clusters.
- Integrate and validate system modules for runtime correctness, memory efficiency, scalability, and stability.
- Profile compilation graphs, training workloads, and runtime execution to identify and eliminate performance bottlenecks.
- Debug vLLM compilation failures on ROCm, CUDA memory leaks, distributed runtime failures, and kernel-level inconsistencies.
- Collaborate with research, infrastructure, and kernel engineering teams to improve throughput, stability, and developer experience.
Requirements
- 5+ years of industry experience in ML systems, distributed training, or related fields.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
- Strong programming experience in Python and C++, with familiarity with ML tooling and distributed systems.
- Deep understanding of profiling tools such as Nsight, ROCm Profiler, XLA profiler, and TPU tools.
- Expertise in partitioning configurations for modern ML frameworks including PyTorch and JAX.
- Experience with multi-node distributed training systems and orchestration frameworks such as DTensor and GSPMD.
- Hands-on experience maintaining or building ML training stacks involving CUDA, ROCm, NCCL, XLA, or similar technologies.
- Extensive XLA/JAX experience, familiarity with distributed serving frameworks such as vLLM, TensorRT, or FasterTransformer, and experience with GPU kernel optimization or accelerator-aware model partitioning are preferred.
- Strong understanding of low-level C++ building blocks used in ML frameworks, including XLA, CUDA kernels, and custom operations, is preferred.
Benefits
- Medical, dental, and vision insurance.
- 401(k) plan.
- Daily lunch, snacks, and beverages.
- Flexible time off.
- Competitive salary and equity.
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