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Technical Program Manager – AI Research
itD is seeking a Technical Program Manager – AI Research to oversee business-critical projects in the AI Research space, facilitating review and approval processes that enable research initiatives to be initiated and shipped successfully. The ideal candidate will bring 5+ years of technical program management experience in a technology environment, including AI compliance reviews, and a track record of managing complex, cross-functional initiatives in ambiguous environments.
Location: onsite presence in New York City 3 days per week.
Pay Rate: $53/hr to $54/hr depends on Experience
We provide comprehensive medical benefits, a 401k plan, paid holidays, and more.
Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.
Responsibilities
- Lead multiple compliance reviews for frontier AI research projects, including drafting requirements, monitoring progress, managing action items, and resolving blockers to keep milestones on schedule.
- Coordinate with requesters, engineering, research teams, reviewers, and privacy stakeholders to clarify requirements and streamline review and approval processes.
- Develop and maintain clear project communications, providing regular updates and weekly reporting on project status, accomplishments, risks, dependencies, and review-process insights.
- Identify project risks and dependencies early, develop mitigation plans, and escalate issues that may affect review timelines or key milestones.
- Research, catalog, and annotate AI Research assets with a high degree of accuracy and attention to detail.
- Analyze data and optimize workflows using Google Sheets and Microsoft Excel, including data exploration, annotation, and reporting.
- Monitor developments in AI research, compliance, and related tooling to identify opportunities for continuous process and project improvements.
Internal Responsibilities
- Attend regular internal practice community meetings.
- Collaborate with your itD practice team on industry thought leadership.
- Complete client case studies and learning material, including blogs and media material.
- Build material to contribute to the Digital Transformation practice.
- Attend internal itD networking events, both in person and virtually.
- Work with leadership on career fast-track opportunities.
Required Qualifications and Skills
- 5+ years of experience in Technical Program Management at a technology company.
- Experience with AI compliance reviews is required.
- Experience managing multiple concurrent, complex technical programs and cross-functional initiatives.
- Advanced proficiency with Google Sheets and/or Microsoft Excel for data analysis, annotation, and workflow management.
- Proficiency with Google Apps, Microsoft Office, web browsers, and AI productivity tools.
- Strong verbal and written communication skills, with demonstrated experience managing stakeholders and building consensus.
- Demonstrated ability to work independently, manage competing priorities, solve complex problems, and operate effectively in ambiguous environments.
Preferred Qualifications and Skills
- Experience with privacy and compliance reviews.
- Experience in Generative AI or broader AI research environments.
- Experience with data analytics, data annotation, or risk management.
- Hands-on experience running ad-hoc queries and analyzing data.
- Experience using AI agents and research tools.
- Data collection and annotation experience.
- Experience working in a large technology or AI-focused organization.
- Previous experience at Meta is preferred.
- PMI or PMP certification.
Education
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field required.
- MBA or advanced degree preferred.
Company Description
About itD: We are part of a new generation of consulting and software development company that blends diversity, innovation, and integrity with real business results. Our structure rejects any strong hierarchy, empowering us to deliver excellent results. We are a woman- and minority-led firm. Every day, we challenge ourselves to be considerate, fair and to re-think what great outcomes mean for our customers. This permeates down to how we approach every interaction, on every project, for every client. You'll thrive here if you are a dynamic self-starter, a difference-maker or someone who wants to deliver great results, without constraints.
The itD Digital Experience: Joining us means you'll be part of our global community, you have a say about your own career journey, and you'll get a chance to give back to causes that matter. You will experience working with Fortune 500 companies and high-performance teams across numerous industries. itD offers our employees excellent benefits such as medical, dental, vision, life insurance, paid holidays, 401K + matching, networking & career learning and development programs. We are growing and we want to see you grow! Visit https://itdtech.com/careers to learn more about what working at itD can mean for you.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law. itD is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please contact us at [email protected] and let us know the nature of your request and your contact information.
Additional Info
Dynamic environment in a culture of respect, empowerment and recognition for a job well done, apply today!
Salary Context
This $110K-$112K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At itD Tech, 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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($111K) sits 48% below the category median. Disclosed range: $110K to $112K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
itD Tech AI Hiring
itD Tech has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $112K - $112K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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