Senior Machine Learning Engineer

at Nvidia

USD 184,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

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AI AWS @ 3 Algorithms @ 4 Communication @ 6 Distributed Systems @ 3 GPU @ 7 Kubernetes @ 3 LLM Machine Learning @ 4 Mathematics @ 4 NVLink Networking Prometheus @ 3 PyTorch @ 4 Python @ 7 Statistics @ 4 TensorFlow @ 4

Details

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning systems that keep NVIDIA’s global DGX Cloud healthy, efficient, and ready for future AI workloads. DGX Cloud combines NVIDIA GPUs, NVLink networking, and the full AI software stack into elastic infrastructure supporting large language models, drug discovery, autonomous driving, and climate science. Your models will transform billions of telemetry signals into predictive insights, enabling customers to innovate while the platform operates more intelligently.

Responsibilities

Research and develop innovative machine learning algorithms and models for NVIDIA’s AI products.
Build production models for anomaly detection, predictive maintenance, and usage optimization.
Develop tools that surface real-time telemetry, efficiency metrics, and long-term trends.
Develop forecasting and simulation models for global-scale planning.
Analyze complex datasets to determine effective approaches for model training and optimization.
Translate findings into clear engineering actions with infrastructure, operations, and product teams.
Participate in cross-functional projects to integrate machine learning capabilities into NVIDIA products.

Requirements

Master’s degree or PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field, or equivalent experience.
8 or more years of 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 and written communication and technical presentation skills.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
Track record of delivering high-impact projects in a fast-paced environment.

Preferred Qualifications

Experience solving capacity planning problems.
Deep understanding of GPU performance metrics.
Familiarity with Prometheus and PromQL.

Compensation and Benefits

Base salary range: USD 184,000–287,500 per year.
Eligibility for equity and benefits.
Applications will be accepted at least until August 7, 2026.
NVIDIA is an equal opportunity employer committed to an inclusive work environment and does not discriminate on the basis of legally protected characteristics.