Deep Learning Product Research Engineer

Details

NVIDIA's Deep Learning Product Research Engineering team operates at the intersection of research, product engineering, and go-to-market. The team develops cutting-edge prototypes, product intelligence, and code-backed guidance that shape NVIDIA products and customer adoption. This role focuses on building prototypes, writing high-quality code, evaluating emerging technologies, explaining complex systems, and turning research ideas into practical product capabilities.

Responsibilities

• Lead product research for generative AI by evaluating emerging models, agent technology, reinforcement learning, and evaluation methods, and assessing their implications 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 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.

Requirements

• Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent experience.
• At least 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 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 developer content, including tutorials, blogs, sample code, white papers, benchmarks, or demos.
• Strong communication and presentation skills, with the ability to explain complex technical topics to expert and non-expert audiences.

Preferred Qualifications

• PhD in Computer Science, Engineering, Machine Learning, Artificial Intelligence, or a related field.
• At least 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 open models, agent frameworks, vector databases, evaluation tools, deployment platforms, and emerging AI developer workflows.

Benefits

• Equity and comprehensive benefits package.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.
• Applications will be accepted at least until September 18, 2026.

The base salary range is USD 136,000–212,750 for Level 3 and USD 160,000–253,000 for Level 4. Base salary is determined by location, experience, and the pay of employees in similar positions.