Deep Learning Product Research Engineer

Posted 6 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
136K-253K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build prototypes, benchmarks, and reference code for generative AI; evaluate models, agentic systems, and deployment; create enablement assets and technical content; translate customer and field signals into product insights and recommendations; collaborate with research, engineering, product, and field teams to improve NVIDIA AI products.
Summary Generated by Built In

NVIDIA is at the center of the AI revolution. Our deep learning platforms, models, frameworks, and accelerated computing technologies help developers, researchers, and enterprises build the next generation of intelligent applications!

The Deep Learning Product Research Engineering (PRE) team sits at the intersection of research, product engineering, and go-to-market. PRE exists to reduce uncertainty about what will make products succeed. Our primary outputs are working cutting-edge prototypes, product intelligence, and code-backed guidance that shape what NVIDIA builds and how customers embrace it. We are looking for a hands-on engineer and generative AI practitioner who can build prototypes, write high-quality code, evaluate emerging technologies, explain complex systems clearly, and turn research ideas into practical product capabilities. In this role, you will create prototypes, demos, white papers, benchmarks, blogs, sample applications, conference material, and other technical content. Work closely with research, engineering, product, marketing, field teams, customers, and the developer community to identify opportunities, surface feedback, and improve products across NVIDIA’s AI ecosystem!

What you'll be doing:

  • Lead product research for generative AI by evaluating emerging models, agent technology, reinforcement learning, and evaluation methods, then assessing what they mean for NVIDIA products.

  • Build proof-of-concept applications, benchmarks, and reference sample code that validate new capabilities and demonstrate product value.

  • Convert customer, developer, benchmark, usage, and field signals into structured product intelligence, including adoption trends, friction points, issue reproductions, and roadmap recommendations.

  • Develop enterprise-ready enablement assets such as reference architectures, integration playbooks, performance tuning recipes, and demo-to-production workflows for Nemotron, NeMo, NIM, and related NVIDIA AI software.

  • Partner with research, engineering, product management, technical marketing, field teams, and customers to turn insights into feature requests, launch inputs, positioning, and usability improvements.

  • Advance internal LLM expertise and tooling through reusable evaluation harnesses, profiling utilities, agentic workflows, and practical analysis of model behavior.

  • Distill hands-on research and engineering work into authoritative technical assets, including code examples, technical write-ups, white papers, demos, talks, and patents where appropriate.

  • Stay current with advances in model training, post-training, inference, agentic systems, evaluation, deployment, safety, and the broader AI developer ecosystem.

What we need to see:

  • Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent experience.

  • 5+ years of proven experience in software engineering, machine learning engineering, AI engineering, solutions architecture, applied research, or a similar technical role.

  • Hands-on experience with machine learning, deep learning, or agentic AI, including building, training, fine-tuning, evaluating, deploying, or optimizing models and AI applications.

  • Practical experience with generative AI systems, including large language models, retrieval-augmented generation, agentic workflows, model evaluation, or AI application development.

  • Experience with Python and modern deep learning frameworks and libraries such as PyTorch, Hugging Face Transformers, LangChain, LlamaIndex, TensorFlow, or similar tools.

  • Familiarity with modern AI-assisted development tools and coding agents such as Codex, Claude Code, Cursor, or similar systems.

  • Ability to create clear, accurate, technically rigorous, and compelling content for developers, including tutorials, blogs, sample code, white papers, benchmarks, or demos.

  • Strong communication and presentation skills, with the ability to explain complex technical topics to both expert and non-expert audiences..

Ways to stand out from the crowd:

  • PhD in Computer Science, Engineering, Machine Learning, Artificial Intelligence, or a related field.

  • 3+ years of hands-on experience with machine learning, deep learning, generative AI, large language models, multimodal models, reinforcement learning, model optimization, or agentic applications.

  • Experience designing or evaluating agentic AI systems, AI coding assistants, model evaluation harnesses, RAG pipelines, synthetic data workflows, or AI safety workflows.

  • Experience with NVIDIA AI software, models, or frameworks such as NeMo, NeMo Retriever, NeMo Guardrails, NeMo RL, NIM, TensorRT, Dynamo, CUDA, cuDNN, or Nemotron models.

  • Familiarity with the broader generative AI ecosystem, including open models, agent frameworks, vector databases, evaluation tools, deployment platforms, and emerging AI developer workflows.

With comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us and, due to unprecedented growth, our product management teams are growing fast. If you're a creative with a genuine passion for technology, 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 136,000 USD - 212,750 USD for Level 3, and 160,000 USD - 253,000 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 4, 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.

Skills Required

  • Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, Artificial Intelligence, or related field, or equivalent experience
  • 5+ years of experience in software engineering, machine learning engineering, AI engineering, solutions architecture, applied research, or similar technical role
  • Hands-on experience building, training, fine-tuning, evaluating, deploying, or optimizing machine learning or deep learning models
  • Practical experience with generative AI systems, including large language models, RAG, agentic workflows, model evaluation, or AI application development
  • Experience with Python and modern deep learning frameworks/libraries such as PyTorch, Hugging Face Transformers, LangChain, LlamaIndex, or TensorFlow
  • Familiarity with AI-assisted development tools and coding agents (e.g., Codex, Claude Code, Cursor)
  • Ability to produce clear technical content for developers: tutorials, blogs, sample code, white papers, benchmarks, demos
  • Strong communication and presentation skills
  • PhD in CS, Engineering, Machine Learning, AI, or related field
  • 3+ years hands-on experience specifically with generative AI, LLMs, multimodal models, reinforcement learning, model optimization, or agentic applications
  • Experience with NVIDIA AI software, models, or frameworks (NeMo, NeMo Retriever, NeMo Guardrails, NeMo RL, NIM, TensorRT, Dynamo, CUDA, cuDNN, Nemotron)
  • Experience designing or evaluating agentic AI systems, evaluation harnesses, RAG pipelines, synthetic data workflows, or AI safety workflows

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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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