Research Engineer, ML Systems (All Industry Levels)
Ist diese Stelle etwas für Sie?
Lebenslauf erstellen Erstellen Sie Ihren Lebenslauf und entdecken Sie Ihre Übereinstimmung mit dieser Stelle — und mit allen anderen.
Die Stelle
Join the ML Systems team to optimize GPU-based AI training and inference at scale.
Develop efficient kernels (Triton, CUDA) and tune performance for models and hardware.
Improve serving with prefix-aware routing and cache-hit optimization for 20K+ QPS.
Train and distill LLMs to reduce latency while maintaining accuracy and engagement.
Build scalable distributed RLHF pipelines and multimodal model training/inference systems.
Collaborate across teams, write clean production-grade code, and contribute to cutting-edge AI solutions.
Develop efficient kernels (Triton, CUDA) and tune performance for models and hardware.
Improve serving with prefix-aware routing and cache-hit optimization for 20K+ QPS.
Train and distill LLMs to reduce latency while maintaining accuracy and engagement.
Build scalable distributed RLHF pipelines and multimodal model training/inference systems.
Collaborate across teams, write clean production-grade code, and contribute to cutting-edge AI solutions.
Die vollständige Anzeige sehen
Aufgaben, Anforderungen, Kompetenzen und Vorteile — mit Ihrem kostenlosen Konto.
oder
Bereits ein Konto?
AnmeldenÄhnliche Stellen
Weitere Positionen, die passen könnten.
? Senior Security Research Engineer ? Research Engineer / Scientist, Frontier Red Team (Cyber) ? Research Engineer, Frontier Red Team (Hardware Lead) ? Research Engineer, Frontier Red Team (Autonomy) ? Research Engineer/Scientist - Generative UI, Consumer Products ? Senior Research Engineer/Scientist - Edge, Consumer Products
HomeofficePartial
StadtRedwood City, US