NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology, and extraordinary people, NVIDIA is looking for a strong technical AI/ML Solution Engineer to join us in shaping the future of software development. Solution Engineers are innovators who can translate business needs into workable technology solutions. Their expertise is deep and broad. They are hands on, producing both detailed technical work and high-level architectural designs.
As an AI/ML Solution Engineer in the AI-Native Development team, you will design and build AI-powered development pipelines, evaluate ML approaches for code generation and review, and drive the adoption of AI-assisted software development across the organization. You will work at the intersection of machine learning and software engineering — selecting the right models, feedback strategies, and evaluation frameworks to make AI-generated code reliable, high-quality, and trustworthy.
What you'll be doing:
Design and build AI-powered development pipelines — from code generation and automated review to feedback loops and evaluation systems.
Evaluate and select ML approaches for specific problems: when to use LLM prompting vs. fine-tuning (QLoRA), classical ML (random forest, linear regression) vs. reinforcement learning, RAG vs. structured extraction.
Architect feedback and evaluation systems that measure and improve AI output quality over time.
Review and refine AI solution architectures — evaluate design decisions, identify weaknesses, propose alternatives with reasoning.
Lead proof-of-concept development to validate new AI/ML approaches for development tooling.
Collaborate with the core team to define risk-based development levels and calibrate AI review depth per level.
What we need to see:
Hold a M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering from a leading university (or equivalent experience).
5+ years of industry experience (or equivalent) in AI pipelines architecture or related fields.
Industry experience building and shipping AI-powered tools or ML pipelines (not just training models — end-to-end delivery).
Strong understanding of LLM capabilities and limitations — prompt engineering, fine-tuning, RAG, agent architectures.
Experience with at least two of: reinforcement learning, classical ML, NLP/information retrieval, evaluation framework design.
Can reason about trade-offs: when to use which approach, with real reasoning backed by shipping experience.
Strong programming skills (Python required; familiarity with ML frameworks — PyTorch, HuggingFace, etc.).
Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Ways to stand out from the crowd:
Experience with LLM-based code generation, code review, or developer tooling.
Familiarity with eval frameworks and feedback loop design (online and offline evaluation).
Experience with AI agent orchestration (multi-agent systems, tool use, planning).
Shown research track record (publications, open-source contributions).
Knowledge of AI-assisted development tools and their underlying architectures.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse 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
- M.Sc. or Ph.D. in Computer Science, Electrical or Computer Engineering
- 5+ years of industry experience in AI pipelines architecture or related fields
- Experience building and shipping AI-powered tools or ML pipelines
- Strong understanding of LLM capabilities and limitations
- Experience with at least two ML approaches such as reinforcement learning, classical ML, NLP
- Strong programming skills in Python
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.
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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.
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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.
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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.”
