Job description

NVIDIA has been transforming computer graphics, PC gaming, accelerated computing, and machine learning for more than 25 years. It’s a unique legacy of innovation fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing – an era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. We’re hiring a Deep Learning Engineer with strong experience in generative AI, LLMs/VLMs, computer vision, and agentic systems. If you’ve spent more time than you’d like to admit building workflows to populate data and/or diversify/expand your dataset, you’ll likely feel at home here. Bonus points if you’ve worked with 3D computer vision (extra bonus if you actually enjoyed it). The team is a balanced mix of engineers and scientists, and we care about both rigor and actually getting things out the door. The culture is collaborative, low-ego, and built around ownership. If you enjoy building systems that get used—and working with people who know when to debate and when to just run the experiment—this jobs is for you. What you will be doing: • Convert research into real products (not just slide decks or notebooks) • Help build workflows that diversify datasets and/or populate data • Ship machine learning workflows/pipelines fast and iterate faster • Leverage LLM/VLM and agents in the data generation pipeline • Define evaluation criteria and run offline evals before any model or prompt change reaches production What we need to see: • Masters degree (or equivalent experience) or preferably a PhD degree in Computer Science or a related field with 5+ years of experience • Solid mathematical and algorithmic foundation and proven expertise 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 to present performance challenges, tradeoffs, and architectural alternatives. • Strong collaboration skills to partner with other teams. Ways to stand out from the crowd: • Experience designing and operating multi-agent pipelines in production, including handling non-deterministic failures, retry logic, and tool-call error recovery" • Shipped a product feature backed by a VLM (e.g., image captioning, document understanding) — including handling inference latency, cost-per-call tradeoffs, and degraded-mode fallbacks • Shipped AI-powered features to real users — not just prototyped with agent frameworks. If your experience is primarily personal projects or hackathons, this role may not be the right fit yet. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 17, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Convert research into real products (not just slide decks or notebooks)
Help build workflows that diversify datasets and/or populate data
Ship machine learning workflows/pipelines fast and iterate faster
Leverage LLM/VLM and agents in the data generation pipeline
Define evaluation criteria and run offline evals before any model or prompt change reaches production
Masters degree (or equivalent experience) or preferably a PhD degree in Computer Science or a related field with 5+ years of experience
Solid mathematical and algorithmic foundation and proven expertise 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 to present performance challenges, tradeoffs, and architectural alternatives.
Strong collaboration skills to partner with other teams.
Experience designing and operating multi-agent pipelines in production, including handling non-deterministic failures, retry logic, and tool-call error recovery"
Shipped a product feature backed by a VLM (e.g., image captioning, document understanding) — including handling inference latency, cost-per-call tradeoffs, and degraded-mode fallbacks
Shipped AI-powered features to real users — not just prototyped with agent frameworks. If your experience is primarily personal projects or hackathons, this role may not be the right fit yet.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 17, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaillmpython

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

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