Senior Principal Development Engineer

Onto Innovation-posted 3 months ago
Full-time • Senior
Wilmington, MA
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Onto Innovation is a worldwide leader in the design, development, manufacture and support of defect inspection, advanced packaging lithography, process control metrology, and data analysis systems and software used by semiconductor device manufacturers worldwide. Onto Innovation provides a full-fab solution through its families of proprietary products that provide critical yield-enhancing information and real time process control responses, enabling microelectronic device manufacturers to drive down the costs and time to market of their products. The Company’s expanding portfolio of equipment and software solutions is used in both the wafer processing and final manufacturing of ICs, and in adjacent markets such as FPD, and LED manufacturing. We design and manufacture advanced semiconductor inspection and metrology tools. Our solutions power innovation for the world’s leading chipmakers. As the industry moves faster than ever, we believe AI will be a key enabler of smarter, faster, and more reliable decision-making in semiconductor manufacturing. We’re building a new AI Innovation Team to explore, develop, and deploy cutting-edge machine learning systems across our product and process ecosystem. You’ll be our founding Lead AI Engineer, responsible for setting the vision, building the team, and delivering impactful AI solutions at scale.

  • Define the AI strategy and architecture for integrating machine learning into core engineering and manufacturing processes.
  • Partner with tool, process, and applications engineers to map as-is processes and define a to-be AI/automation architecture and deliver measurable outcomes.
  • Ship agentic assistants for use-cases.
  • Stand up LLM + RAG + tool integrations (via MCP servers) that help engineers accelerate tool operation/setup/maintenance and explain trade-offs, grounded in internal docs, logs, and historical inspection outcomes.
  • Lead projects across diverse areas: Predictive maintenance for tool health monitoring and failure detection.
  • Computer vision for wafer defect detection, segmentation, and classification.
  • LLM-based engineering assistants using RAG and MCP agents to make internal knowledge more accessible.
  • Process optimization & yield improvement through data-driven insights and parameter tuning.
  • Simulation and digital twins to model process behaviors and accelerate R&D.
  • Build retrieval-augmented AI assistants to query internal knowledge bases, tools, and logs.
  • Architect robust pipelines for data ingestion, labeling, storage, and retrieval across massive multi-modal datasets (images, telemetry, recipes, logs).
  • Stand up scalable MLOps infrastructure: model registries, monitoring, evaluation, deployment, and governance.
  • Hire, mentor, and manage a team of 3 engineers focused on LLM/Agents, CV/ML, and MLOps/Data.
  • Work cross-functionally to integrate AI solutions into production environments safely and securely.
  • 5+ years applied ML/AI experience, with 3+ years in a technical leadership role.
  • Hands-on expertise with at least two of the following domains: Large Language Models - RAG, fine-tuning, agent frameworks, prompt optimization.
  • Predictive Modeling - tool failure prediction, anomaly detection, time-series analysis.
  • Computer Vision - defect detection, segmentation, or SEM/optical imaging.
  • Strong background in ML systems architecture and production deployment.
  • Advanced Python proficiency: C++/CUDA familiarity is a plus.
  • Experience with MLOps stacks: containers, CI/CD, Ray Serve/Triton, model registries (e.g., MLflow), and GPU optimization.
  • Strong stakeholder collaboration skills and the ability to translate between engineering, operations, and leadership.
  • Demonstrated success delivering AI-powered products into production.
  • Familiarity with semiconductor manufacturing, inspection, or metrology.
  • Understanding of fab interfaces and data connectivity (SECS/GEM, GEM300).
  • Prior experience deploying digital twins or simulation-driven optimization.
  • Knowledge of vector databases, retrieval pipelines, and hybrid search.
  • Experience implementing safety, security, and IP protections for AI systems.
  • Exposure to datasets or tools from KLA, ASML, Applied Materials, Onto, Nova, or similar inspection/metrology vendors.
  • Competitive salaries
  • Generous benefits package, including health/dental/vision/life/disability
  • PTO
  • 401K plan with employer match
  • Employee Stock Purchase Program (ESPP)
  • Health & wellness initiatives
  • Collaborative working environment
  • State-of-the-art tools & equipment
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