Qureos

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Member of Technical Staff (Winter Internship)

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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.

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