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About
Optimize and implement high-performance machine learning models for real-time inference Manage the full lifecycle of model deployment, from research integration to production reliability Collaborate with cross-functional teams to address complex engineering challenges and improve system performance
Required Qualifications
PhD in Computer Science, Physics, Math, or equivalent practical experience in backend or ML systems Hands-on experience with inference optimization techniques and modern serving frameworks Proficiency in programming languages such as C++, CUDA, Rust, or optimized Python Experience with distributed systems, Kubernetes, and scaling multi-GPU/multi-node inference Professional fluency in English (written and spoken)
Languages
- English
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