Machine Learning Engineer
Machine Learning Engineer optimizes ML models for speed and efficiency through low-level CUDA kernel tuning, GPU scheduling, and hardware-aware systems design. Requires 2+ years in ML infrastructure with Python/C++/Rust and distributed frameworks like PyTorch.
About the job
Requirements
- Strong background in systems-level ML engineering.
- Experience with CUDA, GPU kernel optimization, and performance tuning.
- Fluency in Python and at least one systems language (C++ or Rust preferred).
- Familiarity with distributed training frameworks (e.g., PyTorch, JAX, DeepSpeed, or similar).
- Experience working with large-scale training or inference infrastructure.
- Understanding of memory management, parallelization, and hardware-aware model optimization.
- 2+ years of experience working in ML infrastructure or performance-critical environments.
- Willingness to work in-person from our SF office in FiDi.
Skills
CUDA, Python, C++, Rust, PyTorch, JAX, Deepspeed, Gpu Optimization, Distributed Training, Memory Management
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