Role overview

Senior Deep Learning Engineer

Requirements and responsibilities

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What you'll be doing:

  • Improve inference speed for Cosmos WFMs on GPU platforms.
  • Effectively carry out the production deployment of Cosmos WFMs.
  • Profile and analyze deep learning workloads to identify and remove bottlenecks.

What we need to see:

  • 5+ years of experience.
  • MSc or PhD in CS, EE, or CSEE or equivalent experience.
  • Strong background in Deep Learning.
  • Strong programming skills in Python and PyTorch.
  • Experience with inference optimization techniques (such as quantization) and inference optimization frameworks, one of: TensorRT, TensorRT-LLM, vLLM, SGLang.

Ways to stand out from the crowd:

  • Familiarity with deploying Deep Learning models in production settings (e.g., Docker, Triton Inference Server).
  • CUDA programming experience.
  • Familiarity with diffusion models.
  • Proven experience in analyzing, modeling, and tuning the performance of GPU workloads, both inference and training.
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Browse stack
FocusDeep LearningRole area
Seniority signalSeniorCandidate level
StackDocker, LLM, PythonPrimary skills
Location1 accepted countryEligibility

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