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About This Role
Job ID: 14279
Business Unit: Metro-North Railroad
Location: New York, NY, United States
Regular/Temporary: Regular
Department: Office of the President
Date Posted: Jan 28, 2026
Description
Job Title:Deputy Chief of Staff
Department: President’s Office
MTA Agency:Metro-North Railroad
Primary Location(s):New York, NY
Salary Range:$165,672- $185,000
Regulated/Safety Sensitive:Non-DOT Regulated/Not Safety Sensitive
Union Affiliation:Non-agreement
Closing Date (if applicable):Until Filled
Shift (if applicable):
Title 55-a (yes or no):No
Other:Telework eligible
ABOUT THE AGENCY
MTA Metro-North Railroad is a dynamic organization, operating out of the jewel of New York City, Grand Central Terminal. We provide service to over 86.5 million customers, traveling in and out of New York and Connecticut. A subsidiary of the Metropolitan Transportation Authority, Metro-North Railroad is one of the busiest commuter railroads in the nation. MTA Metro-North Railroad strives to provide a safe and reliable commute, excellent customer service, and rewarding opportunities to its employees.
JOB SUMMARY
The purpose of this position is to serve as an advisor and executive team partner, supporting the Chief of Staff and the Office of the President at MTA Metro-North Railroad. As part of the Office of the President, the Deputy has broad responsibility and will be critical to developing performance management metrics, business and continuous improvement processes, and initiatives to deliver service effectively, and will act on behalf of the Chief of Staff in their absence. As an agency liaison, the Deputy will cultivate relationships with key internal and external stakeholders throughout the Metro-North organization, MTA agencies, and partners. The Deputy will coordinate internal and external communications for the advancement of Metro-North's mission and MTA priorities.
DUTIES AND RESPONSIBILITIES
- Drive and promote the President's key change management initiatives and communications.
- Provides leadership to facilitate the development of capacity-building within the organization.
- Ensure continuous improvement processes, organizational change, and strategic initiatives of the President and Chief of Staff with a strong ability to formulate resolutions that address complex and abstract challenges within Metro-North’s portfolio.
- Develop and plan initiatives to implement the MTA Strategic Priorities and MNR Strategic Vision in coordination with MTA Headquarters and MNR senior leadership.
- Develop and supervise the development and preparation of high-quality executive-level talking points and presentations, including but not limited to content for monthly MTA Board and Committee Meetings and external speaking engagements.
- Assist in planning and executing employee engagement initiatives. Organize agency-specific employee programs such as awards ceremonies, open house, holiday train.
- Act as a liaison with external stakeholders and build relationships between the President’s office and other MTA agencies, to ensure operational excellence.
- Collaborate with the MTA Headquarters Office of the Customer and the Communications Tower: Align messaging strategies to support a well-informed, engaged workforce.
- Drive special projects and initiatives that span operational departments.
- Performs other duties as assigned.
- Complies with all policies and standards.
- May be required to work hours outside regular work hours, as applicable.
- Observes the work performed by contractors, as applicable.
- Reviews invoices and approves them if the work has contractual standards, as applicable.
- Addresses performance issues with the contractor when possible, as applicable.
- Escalates issues to other parties when needed, as applicable.
KNOWLEDGE, SKILLS AND ABILITIES
- A comprehensive, integrative thinker with proven ability to collaborate with a broad range of diverse stakeholders, employees, and public and governmental officials, and demonstrated ability to build strong partnerships.
- Excellent project management skills with the ability to plan and manage projects by aligning business goals with solutions to achieve successful outcomes.
- Act as a critical thought partner and change agent to drive process improvements and achieve organizational change.
- Proven team leader with excellent written communication, presentation, facilitation, and leadership skills in building team issue escalation and achieving resolution with executive leadership.
- Strong business acumen with proven ability to exercise judgment and discretion while simultaneously balancing competing or shifting priorities.
- Must have focus and strong time management skills, excellent EQ, team building, problem-solving, and prioritization abilities.
- Possesses solid interpersonal capacity with the drive to succeed and deliver results.
- Perform other duties as assigned.
- Extensive experience working in a large multi-disciplinary organization, developing strategy, implementing change management, organizational effectiveness, and continuous improvement.
- High-level political acumen through experience in a high-pressure, high-visibility public administration environment, understanding of media climate, and governmental and industry relations.
REQUIRED EDUCATION AND EXPERIENCE
- Bachelor’s Degree in Arts/Sciences (BA/BS) in Business Administration, Public Administration, Planning, Finance, or satisfactory equivalent degree.
- Minimum 8 years in an increasingly responsible business role and/or education with emphasis on oversight of operations, finance, planning, development design and project management.
- Minimum 7 years managing a professional staff, projects, or administrative function.
LICENSES AND CERTIFICATIONS
- Required: None
- Preferred: Valid driver’s license
BENEFITS - Managerial Benefits
Transportation & Financial Benefits
- Commuting Made Easy – Enjoy a complimentary MTA transportation pass, plus access to tax-advantaged commuter benefits to maximize your savings.
- Premium Health Coverage at Low Cost – Access high-quality individual, family and domestic partner healthcare, dental, vision and life insurance plans.
- Secure Your Future – Build long-term financial security through pension plans and retirement savings accounts designed for eligible employees.
Time Off & Work-Life Balance
- Generous Time Away – Recharge with substantial paid time off and comprehensive holiday schedules that support your personal and family commitments.
- Holistic Support Services – Access our dedicated Work Life Services team and Office of the Chaplains unit for personal guidance and support when you need it most.
Professional Growth & Development
- Learning & Development Program – Advance your career through structured professional development opportunities, skills training, and leadership programs tailored to support your growth within the organization.
- Educational Investment – Pursue your career goals with in-house training and professional development, tuition reimbursement support, and partnerships with educational institutions.
Employee Experience & Community
- Employee Assistance Programs – Comprehensive support services to help you navigate life's challenges with confidence and resources.
- Discounts & Perks – Take advantage of MTA employee discount programs offering savings on products and services.
- Connect & Belong – Join our vibrant Employee Resource Groups to build meaningful connections, share experiences, and contribute to an inclusive workplace culture.
OTHER INFORMATION
- Pursuant to the New York State Public Officers Law & the MTA Code of Ethics, all employees who hold a policymaking position must file an Annual Statement of Financial Disclosure (FDS) with the NYS Commission on Ethics and Lobbying in Government (the “Commission”).
- Final salary is determined experience, skillset, and alignment with compensation practices. The posted range reflects expected compensation and may be updated as market or business needs evolve.
- Employees driving company vehicles will be subject to License Monitoring and must complete defensive driver training once every three years for current MTA drivers; or within 180 days of hire or transfer for an employee entering an authorized driving position.
- To be eligible for consideration for a new role, current MTA employees must complete at least one year of service in their current role prior to applying. Additionally, eligibility to interview is contingent upon maintaining a satisfactory record of job performance, attendance, and disciplinary conduct.
EQUAL EMPLOYMENT OPPORTUNITY/ADA DISCLAIMER
MTA and its subsidiary and affiliated agencies are Equal Opportunity Employers and encourage qualified applicants from diverse backgrounds, experiences, and abilities, including military service members, to apply.
If you seek a reasonable accommodation for a medical condition or disability, or for a religious practice or observance, to participate in the job application or interview process, please notify your MTA representative once you have been contacted regarding the role.
HOW TO APPLY:
For Internal Applicants: Log in to the My MTA Portal, click on the My Job Search tile, select the Careers link, search for the desired position, click Apply, and follow the on-screen instructions.
For External Applicants: Visit www.mta.info, click the “Careers” link located in the footer under the "The MTA" section, then click on “See All Open MTA Positions”. Search for the desired position, click Apply, and follow the instructions.
Salary Context
This $165K-$185K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Metropolitan Transportation Authority, 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 $154,000 based on 8,743 positions with disclosed compensation. C-Level-level AI roles across all categories have a median of $259,000. This role's midpoint ($175K) sits 14% above the category median. Disclosed range: $165K to $185K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Metropolitan Transportation Authority AI Hiring
Metropolitan Transportation Authority has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span College Point, NY, US, New York, NY, US. Compensation range: $107K - $185K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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