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Location:Pittsburgh, PA, US, 15238
Business Unit: Nul
Posting Date: Jun 16, 2026
Job Description:We are seeking a Division Vice President of Information Technology to lead the strategic and operational direction of IT across the Process \& Analytical Instruments (P\&AI) Division, a global portfolio of businesses operating in highly technical, manufacturing\-driven markets. This leader will serve as the primary IT partner to the Division President and business leadership team, ensuring technology investments directly enable growth, margin expansion, operational excellence, and acquisition integration. A critical mandate for this role is the leadership and execution of complex ERP transformations, including SAP S/4HANA implementations, while advancing a modern, secure, and data\-enabled technology landscape. The role operates within AMETEK’s federated IT model, requiring the ability to balance division autonomy with enterprise standardization, particularly across ERP, cybersecurity, data, and shared services. Success will be measured by business outcomes, ERP execution excellence, cybersecurity resilience, and the ability to drive disciplined transformation across a decentralized environment.
Key Responsibilities:
Division IT Strategy \& Business Partnership
- Develop and execute a multi\-year IT strategy aligned to P\&AI business priorities, including growth, productivity, and portfolio optimization
- Partner with Division and Business Unit leadership to identify and enable technology\-driven improvements in operations, commercial effectiveness, and supply chain performance
- Translate business needs into a prioritized, outcomes\-based IT roadmap with measurable financial and operational impact
ERP Transformation Leadership
- Lead end\-to\-end ERP strategy and execution, including:
+ SAP S/4HANA greenfield and/or migration programs
+ Rationalization of legacy ERP environments
+ Standardization of core business processes across the division
- Ensure ERP programs are delivered with strong governance, on\-time execution, and budget discipline
- Drive alignment with enterprise ERP strategy, enabling cross\-division consistency and scalability
- Partner closely with corporate IT and finance leadership to improve data quality, financial close processes, and operational visibility
IT Operations \& Digital Enablement
- Oversee all IT systems, infrastructure, and applications supporting the Division’s global operations
- Ensure a secure, highly available, and resilient IT environment, including business continuity and disaster recovery
- Drive digital transformation initiatives across manufacturing, engineering, and supply chain
- Enable increased automation, data visibility, and decision support across business processes
Cybersecurity, Governance \& Compliance
- Ensure alignment with AMETEK corporate cybersecurity and IT governance standards
- Maintain a strong security posture, including:
+ Vulnerability management
+ Access controls and data protection
+ Incident response readiness
- Partner with Corporate IT to drive compliance with policies, controls, and regulatory requirements
Data, Analytics \& AI Enablement
- Partner with Enterprise Data \& Analytics leadership to:
+ Enable adoption of the enterprise data platform
+ Ensure data standardization and governance across P\&AI
- Drive the use of analytics and AI to improve business decision\-making, productivity, and performance
- Ensure division participation in enterprise KPI standardization and data initiatives
M\&A Integration
- Lead IT due diligence and integration for acquisitions, including:
+ Systems assessment and roadmap definition
+ ERP and infrastructure integration
+ Cybersecurity risk evaluation
- Enable rapid integration to support synergy capture and operational continuity
Organization Leadership
- Build and lead a high\-performing, globally distributed IT organization
- Operate effectively in a federated model, influencing both direct and dotted\-line IT resources
- Drive a culture of accountability, continuous improvement, and disciplined execution
- Develop strong business\-facing IT leaders embedded within operating units
Qualifications \& Experience (Required):
- 15\+ years of progressive IT leadership experience in global, manufacturing or industrial environments
- Proven leadership of large\-scale ERP transformations, including:
+ SAP S/4HANA implementations (greenfield or brownfield)
+ Multi\-site, multi\-business unit ERP standardization
- Strong understanding of manufacturing, supply chain, and engineering\-driven businesses
- Experience operating in a decentralized or federated organizational model
- Demonstrated ability to align IT investments to measurable business outcomes
- Experience leading global, multi\-site IT organizations
- Bachelor’s degree in Information Systems, Engineering, or related field; MBA preferred
Compensation
Employee Type: Salaried
Currency: USD
Salary Minimum: 225,000
Salary Maximum: 300,000 \+
Incentive: Yes
Disclaimer: Where a specific pay range is noted, it is a good faith estimate at the time of this posting. The actual salary offered will be based on experience, skills, qualifications, market / business considerations, and geographic location.
For more information on AMETEK's competitive benefits, please click here.
AMETEK, Inc. is a leading global provider of industrial technology solutions serving a diverse set of attractive niche markets with annual sales over $7\.5 billion.
AMETEK is committed to making a safer, sustainable, and more productive world a reality. We use differentiated technology solutions to solve our customers’ most complex challenges. We employ 22,000 colleagues, in 35 countries, that are grounded by our core values: Ethics and Integrity, Respect for the Individual, Inclusion, Teamwork, and Social Responsibility. AMETEK is a component of the S\&P 500\. Visit https://www.ametek.com/careers for more information.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. Individuals who need a reasonable accommodation because of a disability for any part of the employment process should call 1 (866\) 263\-8359\.
Salary Context
This $225K-$300K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 2130 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 4,133 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At AMETEK, 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 in Demand for This Role
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 $185,000 based on 13,200 positions with disclosed compensation. This role's midpoint ($262K) sits 42% above the category median. Disclosed range: $225K to $300K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
AMETEK AI Hiring
AMETEK has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Pittsburgh, PA, US. Compensation range: $300K - $300K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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