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About This Role
Job ID: 13551
Business Unit: MTA Headquarters
Location: Flushing, NY, United States
Regular/Temporary: Regular
Department: Labor Relations NYCTA
Date Posted: Jan 28, 2026
Description
POSTING NO.
13551
JOB TITLE:
Manager, Labor Relations & Employee Availability - MTA Bus
DEPT/DIV:
Labor Relations
WORK LOCATION:
College Point Depot
FULL/PART-TIME
FULL
SALARY RANGE:
$100,000 to $107,000
DEADLINE:
Until filled
This position is eligible for teleworking, which is currently one day per week. New hires are eligible to apply 30 days after their effective hire date.
Opening:
The Metropolitan Transportation Authority is North America's largest transportation network, serving a population of 15.3 million people across a 5,000-square-mile travel area surrounding New York City, Long Island, southeastern New York State, and Connecticut. The MTA network comprises the nation’s largest bus fleet and more subway and commuter rail cars than all other U.S. transit systems combined. MTA strives to provide a safe and reliable commute, excellent customer service, and rewarding opportunities.
Position Objective:
This position is responsible for advising MTA Bus Company management regarding the administration of sick and other contractual leave provisions, policies, and procedures for represented employees, as well as leave policies and procedures for non-represented and managerial employees, as needed. This position will advise and assist in addressing and recommending appropriate action regarding time and attendance, and other availability related issues.
Responsibilities:
- Formulate, implement, and manage programs to monitor, audit, investigate, and address employee fraud, malingering, theft of wages, chronic absenteeism, and sick leave abuse.
- Advise management on the proper and consistent implementation and administration of applicable contract provisions and policies, employee availability issues, and related discipline and grievances.
- Manage and conduct Sick and Workers Compensation home and fraud investigations and sick leave medical documentation investigations; perform investigatory interviews; arrange for surveillance; prepare related reports; and recommend appropriate action.
- Draft, Review, research, respond, and resolve time and attendance related disciplinary and contractual interpretation cases, related complaints, and information requests.
- Represent the Company in the discipline and grievance process and participate in the preparation of cases for arbitration, including testifying at all steps of the grievance and discipline process, up to and including arbitration.
- Generate and distribute related reports.
- Assist as needed with other Labor Relations matters.
- Perform special projects as required
Qualifications:
Knowledge/Skills/Abilities:
- Excellent oral and written communication skills.
- Excellent organizational and presentation skills.
- Demonstrated ability to work with all internal levels within a given organization.
- Demonstrated proficiency in the administration and interpretation of collective
bargaining agreements, policies, and procedures, especially related to labor
relations, human resources, leave and employee availability, and workers
compensation.
- Demonstrated ability to communicate and interact well with external agencies.
- External agencies may include the Governor’s Office for New York State, the New York City government, elected and other public officials, as well as any staff.
located at other federal or state agencies or authorities.
- Demonstrated ability to work effectively in a high-profile, high-pressure
environment.
- Demonstrated ability to communicate effectively with key internal and/or
external stakeholders.
- Experience conducting, supervising, and training staff in conducting audits,
investigations, and interviews.
- Knowledge of disciplinary and grievance procedures and practices, and
experience testifying at administrative hearings.
- Demonstrated analytical capabilities, quantitative and investigative skills.
- Demonstrated proficiency in Microsoft Office Suite or comparable applications,
i.e., Word, Excel, PowerPoint, and Outlook
Required Education and Experience:
- Bachelor’s degree in Labor Relations, Human Resources, or related field and an equivalent combination of experience and education from an accredited college may be considered in lieu of a degree.
- Minimum 5 years related experience, including at least 2 years in a managerial and/or leadership role in a large, multi-faceted, fast-paced organization or governmental body preferred.
Preferred:
- Thorough knowledge of MTA Bus/NYCT collective bargaining agreements,
policies, procedures, especially those related to labor relations, human
resources, leave and employee availability, and workers' compensation.
- Knowledge of applicable city, state, and federal regulations, including FMLA and
ADA.
- Strong investigative skills
- Familiarity with the MTA’s policies and procedures.
- Familiarity with the MTA’s collective bargaining procedures.
Other Information
May need to work outside of normal work hours (i.e., evenings and weekends)
Travel may be required to other MTA locations or other external sites.
According 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”).
Employees driving company vehicles must complete defensive driver training once every three years for current MNR drivers, or within 180 days of hire or transfer for an employee entering an authorized driving position.
Equal Employment Opportunity
MTA and its subsidiary and affiliated agencies are Equal Opportunity Employers, including those concerning veteran status and individuals with disabilities.
The MTA encourages qualified applicants from diverse backgrounds, experiences, and abilities, including military service members, to apply.
Salary Context
This $100K-$107K range is in the lower quartile 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. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($103K) sits 33% below the category median. Disclosed range: $100K to $107K.
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
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 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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