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
Questions fréquentes
Why are you reporting this job?
Explore further
Salaries, guides and searches in the United States.
Salaries by job title
Apply in 30 seconds
Enter your email to apply. An account will be created automatically.
By continuing, you accept our terms of use.
Already have an account? Login
A question about this job?
Ask it here: you will get the full job summary by e-mail, right away.
Published 3 days ago
Expires 1 month from now
10 views · 0 interested
Boost your chances
Upload your CV — we will match you with relevant openings.
Analyzing your CV...
relace
San Francisco