Job description

Onto Innovation is a leader in process control, combining global scale with an expanded portfolio of leading-edge technologies that include: 3D metrology spanning the chip from nanometer-scale transistors to micron-level die-interconnects; macro defect inspection of wafers and packages; metal interconnect composition; factory analytics; and lithography for advanced semiconductor packaging. Our breadth of offerings across the entire semiconductor value chain helps our customers solve their most difficult yield, device performance, quality, and reliability issues. Onto Innovation strives to optimize customers’ critical path of progress by making them smarter, faster and more efficient. Job Summary & Responsibilities Lead AI Engineer — Semiconductor AI Innovation Driving AI-Powered Solutions for Semiconductor Equipment Operations Location: Wilmington, MA (On-site) Team: AI & Advanced Analytics Reports to: Senior Director, Engineering Direct Reports: Will hire and lead a team of 3 AI/ML engineers About Us 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. About the Role This is a hands-on technical leadership role. You will work closely with senior tool designers, process engineers, and applications teams to understand complex workflows and data flows. You’ll architect, prototype, and productionize AI solutions that accelerate innovation, improve yields, and reduce tool downtime. You will also grow and mentor a team of three engineers specializing in LLMs, computer vision, predictive modeling, and MLOps. Responsibilities 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. Minimum Qualifications 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 . Nice-to-Haves 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 . What Success Looks Like 90 days: Map high-value AI opportunities, propose architecture, and deliver a prioritized roadmap. 6 months: Deliver first production pilot (e.g., predictive tool health, RAG assistant, or wafer defect CV model) and hire first two engineers. 12 months: Multiple AI-powered systems integrated into engineering workflows, delivering measurable impact on yield, efficiency, and downtime . Our Tech Stack LLMs & Agents: OpenAI, Anthropic, HuggingFace, MCP-based connectors, LangChain, LlamaIndex Predictive Models: PyTorch, TensorFlow, Scikit-learn, XGBoost, Time-series ML Computer Vision: PyTorch, OpenCV, Kornia, segmentation/detection architectures Data & Serving: Triton, Ray Serve, MLflow, Kubernetes, Kafka, vector DBs, GPU compute clusters Why Join Us Build foundational AI infrastructure in one of the most data-rich industries in the world. Lead the team shaping the future of AI-assisted semiconductor engineering . Tackle multi-modal AI challenges at scale —from LLMs to predictive analytics to advanced vision systems. Collaborate with world-class engineers pushing the limits of nanometer-scale inspection and manufacturing. Qualifications see above Onto Innovation Inc. offers competitive salaries and a generous benefits package, including health/dental/vision/life/disability, PTO, 401K plan with employer match, and an Employee Stock Purchase Program (ESPP) along with health & wellness initiatives. We provide a collaborative working environment along with resources, and state-of-the-art tools & equipment to promote success; and a welcoming, inclusive corporate culture where individuals are recognized for their contributions. Onto Innovation Inc. is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis. For positions requiring access to technical data, Onto Innovation Inc., Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

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Job Summary & Responsibilities
Lead AI Engineer — Semiconductor AI Innovation Driving AI-Powered Solutions for Semiconductor Equipment Operations
Location: Wilmington, MA (On-site)
Team: AI & Advanced Analytics
Reports to: Senior Director, Engineering
Direct Reports: Will hire and lead a team of 3 AI/ML engineers
Responsibilities 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.
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.
Minimum Qualifications 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.

Nice-to-haves

Advanced Python proficiency: C /CUDA familiarity is a plus.
Nice-to-Haves Familiarity with semiconductor manufacturing , inspection, or metrology.

Application prep

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Keywords to mirror

aimlmachine learningllmpythonci/cdkubernetesgo

Platform: workday
Effort: long

Benefits

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Dental

Vision

401k

Pto

Wellness