Interested in this AI/ML Engineer role at STERIS?
Apply Now →Skills & Technologies
About This Role
Position Summary
The Vice President & Chief Data and Artificial Intelligence Officer (CDAIO) is the executive leader responsible for STERIS’s enterprise data and artificial intelligence strategy, establishing the capabilities, governance, platforms, and operating model required to scale trusted data, advanced analytics, and AI across the company. Reporting to the Chief Information Officer, this role owns the enterprise data-to-AI value chain, including data governance, data management, analytics platforms, AI architecture, AI enablement, adoption, and value realization.
The CDAIO transforms data and AI from fragmented, project-based activities into a governed enterprise capability that accelerates business performance, strengthens decision making, improves operational efficiency, and enables innovation across STERIS. This role partners closely with business leaders, technology executives, Legal, Compliance, and Quality to ensure data and AI investments align with corporate strategy, regulatory requirements, and business outcomes. The CDAIO also leads the development of STERIS’s AI Center of Excellence and drives enterprise adoption of AI technologies and practices that make STERIS faster, smarter, and more competitive.
This is a remote role with approximately 25% domestic and 15% international travel.
What You'll Do As a VP & CDAIO
- Define and lead the enterprise data, analytics, and AI strategy and roadmap.
- Establish data and AI governance, standards, policies, and risk-management practices.
- Build the enterprise data foundation across data governance, master data, data management, and analytics platforms.
- Lead the AI Center of Excellence and advance prioritized AI opportunities from concept through governed production and measurable value.
- Partner with business leaders, Legal, Compliance, Quality, and technology leadership to align investments with business and regulatory requirements.
- Drive enterprise AI adoption, enablement, and workforce literacy.
- Build and lead a scalable global data and AI organization.
- Manage data and AI investments, technology vendors, consulting partners, and platforms.
The Experience, Skills and Abilities Needed
Required:
- Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field, or equivalent relevant experience.
- 15+ years of progressive technology leadership experience, including 5+ years leading data, analytics, or AI functions at enterprise scale.
- Demonstrated experience building or leading an enterprise data and/or AI organization.
- Experience taking AI or advanced analytics initiatives from concept through governed production with measurable business value.
- Experience establishing data governance, data management, or master data across a complex organization.
- Experience operating within a regulated environment with compliance, privacy, and risk obligations.
- Strong knowledge of data governance, machine learning, generative AI, and emerging AI capabilities.
- Proven executive influence, business acumen, cross-functional partnership, and change leadership.
Preferred
- Experience in medical device, life sciences, healthcare, or another highly regulated industry.
- Establishing an AI Center of Excellence or formal AI governance framework.
- Leading globally distributed teams.
- Experience with enterprise platforms, modern data architectures, Salesforce, and ERP environments.
- Experience with Snowflake, Tableau, Power BI, or similar platforms.
- Master's degree or PhD in a data, analytics, engineering, or business discipline.
What STERIS Offers
We value our employees and are committed to providing a comprehensive benefits package that support your health, well-being, and financial future.
Here is just a brief overview of what we offer:
- Market Competitive Pay
- Extensive Paid Time Off (PTO) and 9 added Holidays
- Excellent Healthcare, Dental and vision benefits
- Long/Short Term Disability Coverage
- 401(k) with a company match
- Maternity & Paternity Leave
- Additional add-on benefits/discounts for programs such as Pet Insurance
- Tuition Reimbursement and continued educations programs
- Excellent opportunities for advancement in a stable long-term career
#LI-Remote
#LI-SC1
Pay range for this opportunity is $225,000 - $300,000. This position is also Long-Term-Incentive and Bonus eligible.
Minimum pay rates offered will comply with county/city minimums, if higher than range listed. Pay rates are based on a number of factors, including but not limited to local labor market costs, years of relevant experience, education, professional certifications, foreign language fluency, etc.
STERIS offers a comprehensive and competitive benefits portfolio.
Open until position is filled.
STERIS is a leading global provider of products and services that support patient care with an emphasis on infection prevention. WE HELP OUR CUSTOMERS CREATE A HEALTHIER AND SAFER WORLD by providing innovative healthcare and life sciences products and services around the globe. For more information, visit www.steris.com.
If you need assistance completing the application process, please call 1 (440) 392.7047. This contact information is for accommodation inquiries only and cannot be used to check application status.
STERIS is an Equal Opportunity Employer. We are committed to equal employment opportunity to ensure that persons are recruited, hired, trained, transferred and promoted in all job groups regardless of race, color, religion, age, disability, national origin, citizenship status, military or veteran status, sex (including pregnancy, childbirth and related medical conditions), sexual orientation, gender identity, genetic information, and any other category protected by federal, state or local law. We are not only committed to this policy by our status as a federal government contractor, but also we are strongly bound by the principle of equal employment opportunity.
The full affirmative action program, absent the data metrics required by § 60-741.44(k), shall be available to all employees and applicants for employment for inspection upon request. The program may be obtained at your location’s HR Office during normal business hours.
Salary Context
This $225K-$300K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At STERIS, 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 $212,000 based on 11,857 positions with disclosed compensation. C-Level-level AI roles across all categories have a median of $250,000. This role's midpoint ($262K) sits 24% above the category median. Disclosed range: $225K to $300K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
STERIS AI Hiring
STERIS has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Mentor, OH, US. Compensation range: $300K - $300K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.