Member of Technical Staff (Spring Internship)

About the role

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.

What You'll Do

• Build scalable infrastructure for AI model training and inference

• Lead technical decisions and architecture choices

What We Look For

Core Technical Expertise

• 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.

Ideal Background

• 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.