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About This Role
Job Title:
Director, AI and Digital EnablementJob Description:
The Role
Entegris is currently seeking a Director, AI and Digital Enablement, to join our MS Business Operations team. The location for this position is MS site preferred but location flexible.
As the Director AI and Digital Enablement you will serve as a strategic leader responsible for developing and driving the division’s digital strategy, with a heavy emphasis on artificial intelligence and machine learning. Partnering closely with R&D, product development, IT, and business unit leaders, you will identify, prioritize, and operationalize AI and ML opportunities that improve efficiency, elevate decision quality, and accelerate growth. Your core mission is to ensure the division captures the full value of AI by translating emerging capabilities into practical, scalable solutions embedded directly into our business operations and workflows.
You will set the strategic direction for the division’s AI and digital transformation, establishing a rigorous and scalable approach to building, deploying, and governing AI and Digital solutions. Acting as a change agent across the division, you will build, mentor, and inspire AI talent, elevate AI fluency across teams, and drive the adoption of new tools, capabilities, and ways of working. You will champion responsible, trustworthy AI practices while ensuring clear communication, strong organizational discipline, and effective decision-making. This role requires a unique blend of proven, hands-on AI expertise, strategic thinking, business and financial acumen, and the ability to lead change to ensure efforts are aligned with business growth and value creation. You will need to develop the division level process and practices for AI and Digital projects to resource, monitor and ensure success.
This role answers the question: As a division, are we capturing the full value of AI and machine learning? Are we building scalable, trustworthy AI capabilities that endure? How can we turn our data and AI investments into durable competitive advantage? How do we manage AI and Digital projects as products to realize the intended value?
What You’ll Do
- Develop and own the division’s digital and AI/ML/Digital strategy – setting the roadmap, priorities, and standards that guide how AI is adopted across the business.
- Identify, evaluate, and prioritize high-impact AI, Digital and machine learning use cases; build business cases and ROI models to guide investment in digital and AI initiatives.
- Lead the design, development, and deployment of AI/ML solutions – including predictive models, automation, agents, and copilots – embedded into day-to-day operations.
- Establish AI governance, standards, and responsible-AI practices, including data quality, security, model validation, and ethical use.
- Partner with IT and data teams on the data infrastructure, pipelines, and tooling needed to make projects scalable, sustainable, and production-ready.
- Build strong working relationships with key functional partners to ensure appropriate prioritization, resources, adoption, and change management for initiatives.
- Serve as a change agent across the division – building, mentoring, and inspiring AI talent while raising AI fluency and championing new ways of working across teams.
- Define sustainable key performance indicators (KPIs) to track AI adoption, model performance, efficiency gains, and value delivered.
- Collaborate with a wide variety of functional areas such as R&D, Engineering, Finance, IT, Manufacturing, Legal and Supply Chain to accomplish business objectives.
What We Seek
- Strategic Thinking – Proven ability to develop and execute a digital and AI strategy, from vision through operational delivery
- Proven AI/ML Skills – Demonstrated, hands-on experience building and deploying AI and machine learning solutions (e.g., ML models, generative AI, agents, copilots, and intelligent automation); fluency with modern AI tooling and platforms
- Learning Mindset – Stays current on the rapidly evolving AI landscape and applies new capabilities pragmatically to create business value
- Leadership – Ability to establish clear direction and set priorities, strong listening skills, ability to energize others, effective communicator with capability to influence across functional and regional areas; humble, results-oriented, and eager to learn and contribute
- Business Acumen – Understanding of P&L, risk assessment, and decision making; a strategic, systems mindset; experience building return on investment models for technology and digital investments
- Change Management – Track record of driving adoption of new tools, processes, and ways of working across teams
- Industry – Experience with MS businesses a plus; experience in the advanced manufacturing or technology industries required
- Technical – Proficiency with data analytics and a programming language such as Python (or equivalent) and ML frameworks; experience with cloud/AI platforms; proficient to advanced knowledge of PowerBI and dashboard development/automation a plus; proficient to advanced Excel and PowerPoint skills
- Proven ability to lead complex initiatives or projects with cross-functional team members; comfortable dealing with a high degree of ambiguity and working through issues
- Education – B.S. in Computer Science, Data Science, Engineering, Statistics, Business Administration, or relevant industry experience; advanced degree a plus
- Experience – Minimum 10 years’ experience
- Other – Ability to travel (25-50%)
Outstanding Candidates Will Have:
- Experience with agent platforms and Google Cloud Platform (GCP), including Vertex AI Agent Builder, is a plus.
- Experience in semiconductor, advanced materials, manufacturing, or global supply chain environments.
- Familiarity with enterprise platforms such as Microsoft Azure AI / Copilot, SAP, and ServiceNow.
- Relevant certifications in product management, AI/ML, or cloud, and experience with Agile and modern product operating models.
Why Work at Entegris
Lead. Inspire. Innovate. Define Your Future.
Not everyone who works for a global company shares the same background, experiences and perspectives. We leverage the differences of our employees to bring new ideas to the table. Every employee throughout the company is encouraged to share input on projects and initiatives. Our decision-making process is truly a collaborative effort as we realize there are leaders at every level of the organization. We put our values at the core of how we operate as an organization — not just when it’s convenient, but in a lasting and meaningful way. We want the time and energy you spend here to have a positive impact on your life inside and outside of the office.
What We Offer
Our total rewards package goes above and beyond just a paycheck. Whether you’re looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals.
- Compensation: $185,000 - $250,000 per year range with actual pay dependent on candidate overall skills for the role
- Generous 401(K) plan with an impressive employer match
- Excellent health, dental and vision insurance packages to fit your needs
- Flexible work schedule and 11 paid holidays a year
- Paid time off (PTO) policy that empowers you to take the time you need to recharge
- Education assistance to support your learning journey
- Values-driven culture with colleagues that rally around People, Accountability, Creativity and Excellence
Entegris does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need Entegris immigration sponsorship (e.g., H1B, TN, STEM OPT, etc.) now or in the future.
At Entegris we are committed to providing equal opportunity to all employees and applicants. Our policy is to recruit, hire, train, and reward employees for their individual abilities, achievements, and experience without regard to race, color, religion, sexual orientation, age, national origin, disability, marital or military status.
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Salary Context
This $185K-$250K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Entegris, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,040 based on 13,780 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. Disclosed range: $185K to $250K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Entegris AI Hiring
Entegris has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Aurora, IL, US. Compensation range: $250K - $250K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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