Senior AI ML Solution Engineer, AI-Native Development

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.
  
  

• 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.
  
  

• 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.