NVIDIA
Senior Deep Learning Engineer
Remote Deep Learning role with clear candidate location fit.
PostedJul 4, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
United Kingdom
Role overview
Senior Deep Learning Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
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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