Tech Stack
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.
AI @ 7
Agentic Systems @ 7
Communication @ 6
Computer Vision @ 7
Deep Learning @ 7
GenAI
Generative AI @ 7
Hiring @ 7
LLM
Linux @ 6
Machine Learning
Python @ 6
- 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
NVIDIA is hiring a Deep Learning Engineer with strong experience in generative AI, large language models (LLMs), vision-language models (VLMs), computer vision, and agentic systems. The role focuses on building production machine learning systems and workflows for dataset diversification, data population, data generation, and evaluation. The team combines engineering and scientific expertise and values rigor, collaboration, ownership, and delivering systems that are used in production.
Responsibilities
- Convert research into real products.
- Build workflows that diversify datasets and populate data.
- Ship machine learning workflows and pipelines quickly and iterate on them.
- Leverage LLMs, VLMs, and agents in data generation pipelines.
- Define evaluation criteria and run offline evaluations before model or prompt changes reach production.
Requirements
- Master's degree or equivalent experience, preferably a PhD, in Computer Science or a related field, with 5+ years of experience.
- Strong mathematical and algorithmic foundation, demonstrated through research publications, internships, or significant project experience.
- Strong background in computer vision and deep learning.
- Excellent programming skills in Python and C/C++.
- Excellent software engineering fundamentals.
- Ability to develop code in Unix/Linux environments.
- Excellent written, visual, and verbal communication skills, including the ability to present performance challenges, trade-offs, and architectural alternatives.
- Strong collaboration skills for partnering with other teams.
Preferred Qualifications
- Experience designing and operating multi-agent pipelines in production, including handling non-deterministic failures, retry logic, and tool-call error recovery.
- Experience shipping a product feature backed by a VLM, such as image captioning or document understanding, including managing inference latency, cost-per-call trade-offs, and degraded-mode fallbacks.
- Experience shipping AI-powered features to real users rather than only prototyping with agent frameworks.
Compensation and Benefits
- Base salary range for Level 3: $152,000–$241,500 USD per year.
- Base salary range for Level 4: $184,000–$287,500 USD per year.
- Eligible for equity and benefits.
- Applications accepted at least until September 17, 2026.
- NVIDIA is an equal opportunity employer.
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