ASIC Gen-AI Data Scientist

Quick Facts

• Role: ASIC Technical Products Engineering supporting GenAI, machine learning, and data analytics solutions for semiconductor engineering workflows

Description

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

Key Responsibilities

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

Requirements

• Bachelor’s with 4+ years or Master’s with 2+ in Electrical Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence, or a related field
• Minimum 2 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 (e.g., Claude Code, Cursor, Gemini CLI or similar tools)
• Practical experience building and launching AI/ML systems involving LLMs, including RAG, agentic workflows, and frameworks

Preferred Qualifications

• 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 (prompt design, benchmarking, validation, or retrieval-augmented systems)
• Experience with data analytics and visualization using pandas, scikit-learn, matplotlib, plotly, or similar ecosystems
• Experience with web application technologies (JavaScript, HTML, CSS)
• Experience designing scalable, enterprise-grade AI/ML systems with reliability, traceability, and operational readiness
• Familiarity with document-processing pipelines, technical knowledge platforms, or retrieval systems for engineering content
• Experience working across systems architecture, engineering, data science, and IT

Benefits

• Choice of medical, dental, and vision plans
• Benefit programs protecting income if unable to work due to illness or injury
• Paid family leave
• Robust paid time-off program and paid holidays

Compensation

• Estimated US base salary range: $119,000 - $286,000 per year
• Additional compensation may include benefits, bonuses, and equity