Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Docker @ 3
Python @ 7
LLM @ 4
PyTorch @ 7
CUDA @ 4
GPU @ 4
Deep Learning @ 4
AI @ 4
vLLM @ 4
TensorRT @ 4
SGLang @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
We are looking for a Senior Deep Learning Engineer to help bring Cosmos World Foundation Models from research into efficient, production-grade systems. You’ll focus on optimizing and deploying models for high-performance inference on diverse GPU platforms. This role sits at the intersection of deep learning, systems, and GPU optimization - working closely with research scientists, software engineers, and hardware experts.
NVIDIA Cosmos is a platform purpose-built for physical AI, featuring powerful generative models. Developers use Cosmos to accelerate physical AI development for autonomous vehicles (AVs), robots, and video analytics AI agents by simulating and reasoning about the physical world.
Responsibilities
- 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.
Requirements
- 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
- 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.
Location & Work Policy
- Location listed: UK, Remote.
- Posting includes #LI-Hybrid (hybrid work policy) and also allows remote.
Salary (as listed in posting)
- For Poland: Level 3 base salary range: 221,250 PLN - 383,500 PLN.
- For Poland: Level 4 base salary range: 292,500 PLN - 507,000 PLN.