Senior Staff Machine Learning Engineer — Enterprise AI at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Master’s or Ph.D. in Computer Science, Operations Research, Industrial Engineering, or a related field, or equivalent experience
10+ years designing, building, and deploying machine-learning models and systems in production
12+ years industry experience
Solid understanding of transformers, attention mechanisms, and modern NLP / LLM techniques
Experience fine-tuning or prompting large language models
Strong Python plus deep-learning frameworks such as PyTorch or TensorFlow
Familiarity with CUDA-accelerated libraries (e.g., TensorRT-LLM) is a plus
Proven track record to take a significant ML component or feature from concept to production
Ability to collaborate effectively with multi-functional teams

Responsibilities

Develop Intelligent AI Solutions – Leverage NVIDIA AI technologies and GPUs to build pioneering NLP and Generative AI solutions—such as Retrieval-Augmented Generation (RAG) pipelines and agentic workflows—that solve real-world enterprise and supply-chain problems
Own Key AI Features – Drive the end-to-end development of LLM-powered applications, chatbots, and optimization engines that improve organizational efficiency and resilience
Design Robust ML Architectures – Create machine-learning and combinatorial-optimization designs targeting high-impact challenges across employee productivity, engineering efficiency, AIOps, and supply-chain operations, etc
Collaborate Across NVIDIA – Work closely with product, research, and engineering teams to translate requirements into ML solutions and deliver measurable business outcomes
Mentor & Share Best Practices – Guide junior engineers and peers on ML design patterns, code quality, and experiment methodology

Skills

Key technologies and capabilities for this role

Machine LearningNLPGenerative AIRAGLLMAgentic WorkflowsCombinatorial OptimizationAIOpsGPUDeep Learning

Questions & Answers

Common questions about this position

What is the salary for this Senior Staff Machine Learning Engineer position?

This information is not specified in the job description.

Is this role remote or does it require working from an office?

This information is not specified in the job description.

What skills and experience are required for this position?

Candidates need a Master’s or Ph.D. in Computer Science or related field, 10+ years designing and deploying ML models in production with 12+ years industry experience, solid understanding of transformers and NLP/LLM techniques, and strong Python skills with PyTorch or TensorFlow.

What does the team collaboration look like at NVIDIA for this role?

You will collaborate across NVIDIA with product, research, and engineering teams to translate requirements into ML solutions and deliver measurable business outcomes, and mentor junior engineers and peers on ML design patterns.

What makes a candidate stand out for this Senior Staff Machine Learning Engineer role?

Stand out with agentic AI mastery using frameworks like LangChain or LangGraph, expertise in LLM inference optimization such as KV caching and quantization, end-to-end ML systems ownership from data ingestion to monitoring, and research impact through publications.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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