Machine Learning Manager Jobs in New York
Machine Learning Manager jobs in New York sit at the center of one of the most active markets in the country, with consistent demand from financial services, healthcare technology, and media companies, at levels from team lead through director. Most hiring concentrates in New York City, particularly Manhattan and Brooklyn, alongside growing hubs in Buffalo and Albany tied to state-backed tech initiatives. Well-established employers with lasting New York footprints include JPMorgan Chase, IBM, and Memorial Sloan Kettering, and the most sought-after specialties are MLOps, natural language processing, and responsible AI governance. Find a role that fits below and apply directly.
Find Machine Learning Manager JobsOverview
Showing 5 of 34+ Machine Learning Manager jobs
Mission Statement
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
About The Team
Safe-and-Sound is the centralized Safety team within the AI Foundations Studio in Personalization. We build machine learning systems that help ensure Spotify experiences and recommendations are safe, responsible, and enjoyable across core surfaces like Home, Search, as well as newer generative AI experiences. We partner closely with Tech Research, Trust & Safety, and Content Platform to develop new approaches in areas like synthetic data, fairness, and responsible AI. Our focus is on building scalable, high-impact systems that support both today’s products and the next generation of AI-driven experiences.
- Design, build, and improve machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences
- Contribute to the platformization of safety systems, enabling scalable and reusable solutions across teams
- Develop and operate high-throughput, low-latency backend services powered by ML models
- Partner with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions
- Work on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models
- Contribute to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches
- Collaborate with foundational model teams to embed safety into LLM-based and agent-driven experiences
- Use metrics and experimentation to continuously improve system performance, safety outcomes, and user experience
Who You Are
- You are experienced in building and deploying machine learning systems in production environments
- You have hands-on experience with both traditional ML approaches and newer generative AI techniques
- You have worked with scalable backend systems that require reliability, low latency, and high availability
- You understand how to apply ML solutions to real-world product challenges, ideally in consumer-facing products
- You have experience with model evaluation approaches such as labeling workflows, red-teaming, or ground truth data generation
- You are comfortable working across disciplines, collaborating with product managers, researchers, and policy partners
- You care deeply about building safe, responsible, and inclusive user experiences
- You bring a thoughtful, metrics-driven approach to problem solving and decision-making
Where You'll Be
- This role is based in New York or Boston
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home
Compensation
- The United States base range for this position is $184,050 – $262,928 USD, plus equity.
Benefits
- The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
Today, we are the world’s most popular audio streaming subscription service.
Mission Statement
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
About The Team
Safe-and-Sound is the centralized Safety team within the AI Foundations Studio in Personalization. We build machine learning systems that help ensure Spotify experiences and recommendations are safe, responsible, and enjoyable across core surfaces like Home, Search, as well as newer generative AI experiences. We partner closely with Tech Research, Trust & Safety, and Content Platform to develop new approaches in areas like synthetic data, fairness, and responsible AI. Our focus is on building scalable, high-impact systems that support both today’s products and the next generation of AI-driven experiences.
- Design, build, and improve machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences
- Contribute to the platformization of safety systems, enabling scalable and reusable solutions across teams
- Develop and operate high-throughput, low-latency backend services powered by ML models
- Partner with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions
- Work on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models
- Contribute to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches
- Collaborate with foundational model teams to embed safety into LLM-based and agent-driven experiences
- Use metrics and experimentation to continuously improve system performance, safety outcomes, and user experience
Who You Are
- You are experienced in building and deploying machine learning systems in production environments
- You have hands-on experience with both traditional ML approaches and newer generative AI techniques
- You have worked with scalable backend systems that require reliability, low latency, and high availability
- You understand how to apply ML solutions to real-world product challenges, ideally in consumer-facing products
- You have experience with model evaluation approaches such as labeling workflows, red-teaming, or ground truth data generation
- You are comfortable working across disciplines, collaborating with product managers, researchers, and policy partners
- You care deeply about building safe, responsible, and inclusive user experiences
- You bring a thoughtful, metrics-driven approach to problem solving and decision-making
Where You'll Be
- This role is based in New York or Boston
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home
Compensation
- The United States base range for this position is $184,050 – $262,928 USD, plus equity.
Benefits
- The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
Today, we are the world’s most popular audio streaming subscription service.
See All 34 Machine Learning Manager Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find Machine Learning Manager JobsMachine Learning Manager Jobs by City in New York
Where New York roles are concentrated, by current openings.
Machine Learning Manager Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
- EY5
- Affirm2
- Capital One2
- Google2
- Spotify2
Top Industries Hiring
- Technology & Software6
- Accounting & Auditing5
- Banking & Financial Services5
- Music3
- Consulting & Professional Services2
What New York Employers Look For
The qualifications that appear most often in machine learning manager jobs across New York.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Proven experience leading and mentoring machine learning or data science teams
- Deep hands-on knowledge of Python, TensorFlow, PyTorch, or comparable ML frameworks
- Experience deploying and maintaining machine learning models in production environments
- Strong cross-functional collaboration with product, engineering, and business stakeholders
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for ML workloads
Machine Learning Manager Jobs in New York: Frequently Asked Questions
How do you become a machine learning manager in New York?
There is no state-issued license required to work as a machine learning manager in New York. The typical path begins with a bachelor's or master's degree in computer science, applied mathematics, or a related technical field, followed by several years as an individual contributor in machine learning or data science. New York employers, especially in finance and healthcare technology, consistently favor candidates who have both hands-on modeling experience and demonstrated team leadership before moving into a management role.
Which companies hire machine learning managers in New York?
Employers hiring machine learning managers in New York right now include EY, Affirm, and Capital One, based on current listings on Migrate Mate as of June 2026. New York's concentration of financial institutions, global media companies, and large hospital networks means demand for machine learning managers is spread across industries rather than confined to pure technology firms.
Which New York cities have the most machine learning manager jobs?
New York, Boston, and Brooklyn have the most machine learning manager openings in New York. New York City dominates because it is home to the headquarters of major financial institutions, advertising technology companies, and academic medical centers that all run large data science organizations, while Buffalo and Albany have seen growth driven by state economic development programs attracting technology employers outside the metro.
Are there remote machine learning manager jobs in New York?
Yes, and more than most fields. About 41% of machine learning manager openings tied to New York are remote or hybrid as of June 2026, reflecting the desk-based and collaborative-but-flexible nature of the work. The parts of the role most compatible with remote arrangements are model strategy, code review, and stakeholder reporting, while on-site expectations tend to apply when close coordination with data engineering or product teams is required.
How can I get hired as a machine learning manager in New York with little or no experience?
The most realistic entry path is to first establish yourself as a strong individual contributor, then step into a team lead role before pursuing a full management title. Large New York employers such as financial institutions and hospital networks regularly hire associate data scientists or machine learning engineers into structured rotational programs where management exposure comes within the first two years. Building a portfolio of end-to-end deployed projects and earning a cloud ML certification strengthens a candidacy significantly in the New York market.
Where can I find and apply to machine learning manager jobs in New York?
You can find and apply to machine learning manager jobs in New York on Migrate Mate, which lists current New York openings updated regularly. Search the listings, find roles that match your experience and preferred location or work arrangement, and apply directly to the ones that fit.
See All 34 Machine Learning Manager Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find Machine Learning Manager Jobs