ASIC Gen-AI Data Scientist

JR110472 ASIC Gen-AI Data Scientist

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

Our vision is to transform how the world uses information to enrich life for all.

Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever!

As part of the ASIC Technical Products Engineering organization, you will help drive the development of next-generation GenAI, machine learning, and advanced data analytics solutions for semiconductor engineering. In this role, you will work on intelligent systems that improve engineering productivity, strengthen technical decision-making, and unlock insights from complex ASIC pre and post silicon engineering workflows.

You will collaborate with cross-functional teams across System Architecture, Logic Design, Analog/Mixed-Signal Design, Data Science and IT to prototype, build, and scale practical AI-driven solutions that improve quality, cost, cycle time, and engineering efficiency.

• GenAI System Development:
  Design, build, and improve GenAI-powered and agentic systems supporting ASIC semiconductor engineering workflows such as code generation, data extraction, analytics, documentation automation, failure triage, root cause analysis, and technical knowledge retrieval.
• LLM Workflow Engineering:
  Build, evaluate, and optimize LLM-based workflows, including prompting, developing skills, retrieval-augmented generation (RAG and Graph-RAG), benchmarking, and quality evaluation.
• Machine Learning Production:
  Develop and implement machine learning and deep learning models for classification, regression, anomaly detection, failure analysis, and engineering decision support.
• Cross-Functional Collaboration:
  
  Partner with domain experts and cross-functional teams to translate complex engineering problems into scalable AI/ML and analytics solutions.
• Production Deployment:
  Support deployment, monitoring, and operationalization of AI/ML solutions in cloud and enterprise environments.
• Technical Communication:
  Communicate technical findings, recommendations, and model outcomes clearly to both technical and non-technical stakeholders.
• Innovation Leadership:
  Identify and drive high-impact opportunities where GenAI, machine learning, and analytics can improve engineering productivity and business outcomes!

• Bachelor's with 10+ years or Master’s degree with 8+ in Electrical Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence, or a related field
• Minimum 4 years of hands‑on experience developing and deploying AI applications in semiconductors, electronics, or other engineering industries.
• Strong programming proficiency in Python.
• Familiarity with modern AI coding tools / agentic coding harnesses, such as Claude Code, Cursor, Gemini CLI, or similar tools.
• Practical experience in developing and implementing AI/ML systems involving LLMs, including RAG, agentic workflows, and frameworks.

• Experience building agentic systems or AI solutions for ASIC semiconductor pre‑silicon and post‑silicon workflows.
• Deep understanding of semiconductor‑specific AI/ML applications
• Cloud experience with GCP, AWS, or Azure, including deploying ML pipelines in production.
• Experience with LLM training, inference, and evaluation workflows, including prompt design, benchmarking, validation, or retrieval‑augmented systems.
• Experien…