Machine Learning Engineer
relace · San Francisco
Job description
About the role
Relace is building high‑performance models and infrastructure for code generation. The Machine Learning Engineer will focus on low‑level optimizations to make models faster, more efficient, and reliable at scale.
Key responsibilities
- Develop and optimize CUDA kernels, memory layouts, and GPU scheduling to improve training and inference performance.
- Optimize compute and networking paths and collaborate with research teams to productionize new model architectures.
- Perform deep performance tuning on large‑scale ML systems and maintain reliable infrastructure.
Required profile
- Strong background in systems‑level ML engineering with at least 2 years of relevant experience.
- Hands‑on experience with CUDA, GPU kernel optimization, and performance tuning.
- Willingness to work onsite from the San Francisco FiDi office.
Required skills
- Python
- C++ or Rust
- CUDA
- GPU kernel optimization
- Distributed training frameworks (e.g., PyTorch, JAX, DeepSpeed)
- Memory management, parallelization, and hardware‑aware model optimization
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Published 3 days ago
Expires 1 month from now
11 views · 0 interested
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relace
San Francisco