Inference optimization with vLLM or TRT-LLM.
Model acceleration: quantization, distillation, caching, and batching.
High-performance systems: C++, CUDA, Rust, or optimized Python; GPU profiling.
Distributed systems and scaling: Kubernetes, Ray; multi-GPU/multi-node inference.
Public work: open-source contributions or deep-dive technical writing.
PhD in CS/Physics/Math or equivalent; English fluency.

🎁 Benefits

Flat structure, fast iterations, minimal process theater.
Impactful work and open-source contributions.
Work is visible with US-based leadership collaboration.
Future relocation/US visa support may be available.

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