As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that keeps NVIDIA’s global DGX Cloud healthy, efficient and ready for the next waves of AI breakthroughs. DGX Cloud fuses NVIDIA GPUs, NVLink networking and the full AI software stack into elastic infrastructure powering large language models, drug discovery, autonomous driving and climate science. Your models will turn billions of telemetry signals into predictive insight. This frees customers to innovate while our platform runs smarter.
What you'll be doing:
Ground breaking and developing innovative machine learning algorithms and models that propel our AI products.
Build production models for anomaly detection, predictive maintenance and usage optimization.
Develop tools surfacing real time telemetry, efficiency metrics and long term trends.
Develop forecasting and simulation models for global scale planning.
Analyzing complex datasets to determine the best approach for model training and optimization.
Translate findings into clear engineering actions with infrastructure, operations and product teams.
Participating in cross-functional projects to integrate machine learning capabilities into various NVIDIA products.
What we need to see:
Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience).
8+ years experience applying Machine Learning to operational systems.
Proven track record of building and deploying Machine Learning models in production environments.
Experience with time series analysis and optimization algorithms.
Familiarity with distributed systems and cloud platforms such as AWS and Kubernetes.
Strong software engineering skills and proficiency in Python.
Effective verbal/written communication, and technical presentation skills.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
A track record of delivering high-impact projects to compete in a fast-paced environment.
Ways to stand out from the crowd:
Experience solving capacity planning problems.
Deep understanding of GPU performance metrics.
Familiarity with prometheus and PromQL.
You will also be eligible for equity and benefits.
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.Skills Required
- Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience).
- 8+ years experience applying Machine Learning to operational systems.
- Proven track record of building and deploying Machine Learning models in production environments.
- Experience with time series analysis and optimization algorithms.
- Familiarity with distributed systems and cloud platforms such as AWS and Kubernetes.
- Strong software engineering skills and proficiency in Python.
- Effective verbal/written communication, and technical presentation skills.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
- A track record of delivering high-impact projects to compete in a fast-paced environment.
- Experience solving capacity planning problems.
- Deep understanding of GPU performance metrics.
- Familiarity with Prometheus and PromQL.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
