Used Tools & Technologies
GenAIRequired 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.
Software Development @ 6
Algorithms @ 4
Mathematics @ 4
PyTorch @ 6
Deep Learning @ 4
Generative AI @ 4
AI @ 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 advance inference optimizations for frontier workloads including multi-agent AI systems, generative multimodal models, and inference-time compute scaling. The role spans algorithmic to system-level work across inferencing engines, systems, and hardware architectures and involves close collaboration with deep learning research, framework development, and silicon architecture teams.
Responsibilities
- Keep up to date on the latest advancements in generative AI research.
- Analyze and prototype emerging workloads in multi-agent AI systems, generative multimodal models, and inference-time compute scaling.
- Develop and pioneer optimizations across the inference stack to improve inferencing quality and speed on NVIDIA systems.
- Collaborate closely with production teams to incorporate the latest advancements into software frameworks.
Requirements
- Master’s degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.
- Strong foundation in deep learning, with particular emphasis on generative models and inferencing.
- At least 5 years of relevant software development experience in modern deep learning frameworks such as PyTorch.
- Growth mindset and a pragmatic attitude.
Ways to Stand Out
- Published research or noteworthy contributions in deep learning (inference-time compute, multimodal generation, AI systems).
- Experience prototyping or deploying agentic (multi-agent) AI systems and/or multimodal generation models.
- Experience collaborating across algorithms, software, and performance teams to deliver high-quality solutions.
- Familiarity with computer architecture and its relationship to AI algorithm development.
Compensation & Other Details
- Base salary range by level and location: 152,000 USD - 241,500 USD for Level 3; 184,000 USD - 287,500 USD for Level 4. Base salary determined based on location, experience, and pay of employees in similar positions.
- Eligible for equity and benefits.
- Location: Redmond, WA, United States (role posting lists Redmond, WA).
- Applications accepted at least until March 6, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to diversity and non-discrimination.