Director, AI & Digital Process Innovation

Entegris

Massachusetts

On-site

USD 184,000 - 246,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Annual bonus eligible

Progressive paid time off

401(K) plan with employer match

Health, dental and vision insurance

Education assistance

Job summary

Entegris seeks a Director of AI & Process Solutions to lead AI-enabled science and engineering initiatives within the Digital Innovation team of Materials Solutions. You will define roadmaps, partner with R&D, and drive autonomous workflows that accelerate discovery, scale-up, and data-driven decision making.

The role requires 10+ years in AI/ML, strong leadership, and a track record translating complex science into practical AI-enabled outcomes.

Qualifications

MS or PhD in Computer Science, Data Science, Artificial Intelligence, Chemistry, Materials Science, Chemical Engineering or related technical discipline.
10+ years of AI/ML, advanced analytics, computational science, or digital innovation experience in R&D or manufacturing environments.
Experience leading multidisciplinary technical teams and delivering scalable AI/analytics solutions across multiple groups.
Strong understanding of ML, generative AI, LLMs, knowledge graphs, semantic search, and modern AI architectures.
Experience translating scientific challenges into practical AI-enabled solutions with measurable outcomes.

Responsibilities

Define AI, ML, generative AI, and process systems strategy across Materials Division R&D.
Build and maintain the roadmap for AI-enabled scientific solutions across MS business units.
Lead deployment of AI-enabled workflows and intelligent assistants to improve discovery and decision-making.
Advance capabilities in process simulation, digital twins, and analytical measurement for product development.
Scale AI and digital process opportunities across discovery, materials design, formulation, and manufacturing readiness.
Partner with product, process, and manufacturing teams to build AI-enabled knowledge assets and decision frameworks.
Transition mature AI models and digital twins from research into production environments.
Apply AI to improve process understanding, yield, and manufacturability.
Establish AI governance, risk management, and cybersecurity alignment across MS.