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Senior AI ML Solution Engineer, AI-Native Development

NVIDIA

Israel, Tel Aviv permanent

Posted: March 25, 2026

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Quick Summary

Design and develop AI/ML solutions for various applications. Use expertise in deep learning and software development to deliver high-quality solutions.

Job Description

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.

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