Member of Technical Staff (Spring Internship)
Wafer•San Francisco, CA
10d
About The Position
Join our team as an intern to build the future of inference, GPU optimization and AI infrastructure. You'll work directly as a full-time engineer with the team to help define our technical direction and build the core systems that power our GPU optimization platform.
Requirements
- GPU Fundamentals: Deep understanding of GPU architectures, CUDA programming, and parallel computing patterns.
- Deep Learning Frameworks: Proficiency in PyTorch, TensorFlow, or JAX, particularly for GPU-accelerated workloads.
- LLM/AI Knowledge: Strong grounding in large language models (training, fine-tuning, prompting, evaluation).
- Systems Engineering: Proficiency in C++, Python, and possibly Rust/Go for building tooling around CUDA.
Nice To Haves
- Publications or open-source contributions in inference GPU computing or ML/AI for code are a plus.
- Hands-on experience with large-scale experiments, benchmarking, and performance tuning.
Responsibilities
- Build scalable infrastructure for AI model training and inference
- Lead technical decisions and architecture choices
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
