Lead AI Engineer responsible for setting vision, building team, and delivering AI solutions at scale in semiconductor manufacturing.
Compensation
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.
Responsibilities
Define 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, computer vision for wafer defect detection, LLM-based engineering assistants, process optimization & yield improvement, simulation and digital twins, build retrieval-augmented AI assistants, architect robust pipelines for data ingestion, labeling, storage, and retrieval across massive multi-modal datasets, stand up scalable MLOps infrastructure, hire, mentor, and manage a team of 3 engineers, work cross-functionally to integrate AI solutions into production environments safely and securely.
Requirements
Nice to have: Familiarity with semiconductor manufacturing
Nice to have: Understanding of fab interfaces and data connectivity
Nice to have: Prior experience deploying digital twins
Nice to have: Knowledge of vector databases
Nice to have: Experience implementing safety, security, and IP protections for AI systems
Lead the technical transition and ownership of CTC’s customer intelligence platform, developing and maintaining ML/GenAI models, pipelines, and production controls.
Compensation
Broadband Salary Range: $64,000 – $106,000.
Responsibilities
Own the platform’s ML and GenAI capabilities
Develop and maintain production-grade Python and PySpark code
Run the production platform end-to-end
Build rigorous ML and GenAI evaluation frameworks
Implement production controls for GenAI
Requirements
Graduate-level education in Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering or related technical discipline
Lead and develop a team of data scientists to deliver advanced analytics, machine learning and AI solutions that create measurable business value.
Responsibilities
Lead and develop a team of data scientists
Oversee end-to-end delivery of complex data science projects
Manage priorities and resources
Establish delivery standards
Ensure analytical solutions are delivered on time, within budget and to a high quality
Requirements
Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or a related quantitative discipline, or equivalent practical experience
Lead the development and integration of AI prototypes and multimodal data pipelines for national security missions.
Compensation
Salary compensation range and midpoint: $143,600 - $179,500 - $215,400 Annual
Responsibilities
Independently develop and integrate prototype capabilities that combine software, data processing, cloud components, and AI methods; apply engineering practices that make them reproducible, testable, and usable by MITRE and sponsor teams.
Assess and adapt research from academia and industry to challenging sponsor data and mission problems.
Design data ingestion, normalization, and ETL workflows for multimodal data; analyze data from multiple mission sources and identify limitations that affect findings.
Select AI methods for mission problems and design experiments to evaluate their performance under sponsor-relevant conditions.
Define and execute technical studies, including hypothesis development, experiment design, implementation, and evaluation.
Requirements
Bachelor’s degree in Computer Science or related field
Master’s degree in Computer Science or related field
PhD in Computer Science or related field
Nice to have: Advanced degree in computer science, engineering, or related disciplines
Nice to have: Experience fusing mission data types such as GEOINT, OSINT, imagery
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