Interested in this AI/ML Engineer role at Moog, Inc?
Apply Now →About This Role
Moog is a performance culture that empowers people to achieve great things. Our people enjoy solving interesting technical challenges in a culture where everyone trusts each other to do the right thing. For you, working with us can mean deeper job satisfaction, better rewards, and a great quality of life inside and outside of work.
Job Title:
Senior Director, AI EnablementReporting To:
Chief Information OfficerWork Schedule:
Hybrid – Buffalo, NYMoog’s Global IT function is seeking a strategic, enterprise\-minded leader to serve as the Senior Director of Artificial Intelligence Enablement.
As the Senior Director of Artificial Intelligence (AI) Enablement, you will build and lead Moog’s new AI Enablement Center from inception — defining strategy, assembling the team, establishing governance, and driving measurable AI value across the enterprise. You must be equally comfortable in the boardroom and in a technical architecture review, and must possess the rare combination of visionary leadership, deep AI fluency, and the operational discipline to deliver results in a complex, regulated aerospace environment.
To qualify for the Senior Director of AI Enablement role, here is what we would expect you to bring to Moog…
- Over 15 years of progressive technology leadership experience, with at least five (5\) years in AI, ML, or data science domains
- Demonstrated success building and leading high\-performing technology organizations (30\+ people) from early stage through maturity
- Deep working knowledge of modern AI/ML technologies, including LLMs, generative AI, MLOps, and AI\-embedded enterprise platforms
- Experience operating in regulated industries (aerospace, defense, healthcare, financial services) with strong understanding of compliance frameworks
- Proven ability to translate complex AI concepts into business value narratives for executive and non\-technical audiences
- Experience managing significant technology investment portfolios ($10M\+)
- The ability to obtain a U.S. security clearance
- Must live local to the Buffalo, NY area, or be willing to relocate, to work onsite.
It would also be beneficial if you had:
- Direct experience with ITAR, EAR, CMMC, or other defense/export control regulatory frameworks
- Prior aerospace, defense, or advanced manufacturing industry experience
- Active TS/SCI clearance
- Executive education or certification in AI strategy, ethics, or governance
As the Senior Director of AI Enablement, you will…
- Lead the end\-to\-end AI Enablement Center, including strategy, team development, portfolio management, and stakeholder engagement across all business units
- Own the enterprise AI roadmap and govern the AI portfolio from ideation through value realization
- Serve as the primary executive sponsor for all three AI use case domains: commercial AI platforms, ITAR\-compliant AI environments, and platform\-embedded AI
- Build, inspire, and retain a world\-class team of AI practitioners, architects, engineers, and change managers
- Establish and chair the AI Governance Board; present to the AI Executive Steering Committee
- Drive relationships with AI platform vendors, research institutions, and industry partners
- Act as the company's AI thought leader — representing the organization at industry events, with customers, and with regulators
- Establish and report on AI KPIs and ROI metrics; ensure AI investments deliver measurable business value
- Ensure all AI activities comply with ITAR, CMMC, export control, and applicable AI regulations
How we care for you:
- Financial Rewards: great compensation package, bonus opportunities, matching 401k, and the ability to participate in Employee Stock Purchase Plan (select locations), Flexible Spending and Health Savings Accounts
- Work/Life Balance: Flexible paid time off, holidays and parental leave program.
- Health \& Welfare: Comprehensive insurance coverage including medical, dental, vision, life, disability, Employee Assistance Plan (“EAP”) and other supplemental benefit coverages.
- Professional Skills Development: Tuition Assistance, mentorship and coaching opportunities, leadership development and other personal growth programs
- Culture: Warm, respectful, family\-like environment driven by our 12 core values. Multiple Employee Resource Groups led by our employees, open and welcoming to all.
Salary Range Transparency:
Buffalo, NY $255,000\.00–$275,000\.00 AnnuallySalary Range Disclaimer
The base salary range represents the low and high end of the Moog salary range for this position in the given work location. Actual salaries will vary depending on factors including but not limited to location, experience, and performance. The range(s) listed is just one component of Moog's total compensation package for employees. Other rewards may include annual bonuses, employee stock purchase plan, an open paid time off policy, and many region\-specific benefits.
This position requires access to U.S. export\-controlled information.
EOE/AA Minority/Female/Sexual Orientation/Gender Identity/Disability/Veteran
*Moog is an Equal Opportunity Employer, and as such affirms the right of every person to participate in all aspects of employment without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, age, veteran status, disability, genetic information, or any other protected characteristic. If you are interested in applying for employment and need special assistance or an accommodation to apply for a posted position, contact our Human Resources department via phone at 844\-367\-5787\.*
No unsolicited agency submittals please. Agency partners must be invited to participate in a search by our Talent Acquisition Team and have signed terms in place prior to any submittal. Absent compliance with these pre\-conditions resumes submitted directly to any Moog Inc. employee or affiliate will not qualify for fee payment, and therefore become the property of Moog Inc.
Salary Context
This $255K-$275K 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 Moog, Inc, 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. Director-level AI roles across all categories have a median of $250,000. This role's midpoint ($265K) sits 43% above the category median. Disclosed range: $255K to $275K.
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.
Moog, Inc AI Hiring
Moog, Inc has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Buffalo, NY, US. Compensation range: $275K - $275K.
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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