Senior Systems Software Engineer - Machine Learning

NVIDIA•Durham, NC

3d•$152,000 - $287,500

About The Position

NVIDIA is hiring an engineer to turn machine-learning research into products, with a focus on generative AI, LLMs/VLMs, computer vision, agentic systems, and data-generation workflows. The team combines engineers and scientists and values rigor, practical delivery, collaboration, low ego, and ownership. The role involves building and rapidly iterating on machine-learning workflows and pipelines, using LLMs, VLMs, and agents in data-generation pipelines, and defining and running offline evaluations before model or prompt changes reach production. The position is open at Level 3 or Level 4. The stated expected base salary ranges are $152,000–$241,500 for Level 3 and $184,000–$287,500 for Level 4. The role is eligible for equity and benefits. Applications will be accepted at least until November 16, 2026. This is an existing vacancy.

Requirements

A master's degree or equivalent experience, or preferably a Ph.D., in Computer Science or a related field, with at least 5 years of experience.
A solid mathematical and algorithmic foundation, demonstrated through research publications, internships, or significant project experience.
A 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.

Nice To Haves

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 handling inference latency, cost-per-call tradeoffs, and degraded-mode fallbacks.
Experience shipping AI-powered features to real users rather than only prototyping with agent frameworks.
Experience with 3D computer vision.

Responsibilities

Convert research into real products.
Help build workflows that diversify datasets and/or populate data.
Ship machine-learning workflows and pipelines quickly and iterate on them.
Use LLMs, VLMs, and agents in the data-generation pipeline.
Define evaluation criteria and run offline evaluations before model or prompt changes reach production.