Machine Learning Manager Jobs in USA with Visa Sponsorship
Machine Learning Manager roles rank among the most actively sponsored positions in tech, with employers filing H-1B visa petitions consistently for candidates who combine technical depth with team leadership. A master's or PhD in computer science, statistics, or a related field typically supports the specialty occupation requirement. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
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.
At Spotify, great personalization is about more than recommending the right song. It's about creating listening experiences that feel effortless and meaningful while balancing the needs of listeners, creators, and our business.
The Samba team, part of Spotify's Personalization Mission, works on multi-objective balancing and sequencing for personalized listening experiences like Autoplay, Radio, and Mixes. Our engineers bring together machine learning, backend engineering, and data engineering to build systems that support Spotify's financial objectives while keeping listeners at the center of what we do.
We're looking for an Engineering Manager to lead this team, develop our engineers, and help shape the technical direction of systems that influence how millions of people experience Spotify.
ROLE AND RESPONSIBILITIES
- Lead and grow a team of machine learning, backend, and data engineers, supporting their development and helping them deliver their best work.
- Shape the team's technical strategy and execution, ensuring engineering efforts align with listener needs and Spotify's broader business goals.
- Guide the development of machine learning and recommendation systems that balance multiple objectives across personalized listening experiences.
- Collaborate with Product and engineering partners to define priorities, align on outcomes, and translate complex challenges into clear plans.
- Support the team in making thoughtful technical decisions across experimentation, scalability, system reliability, and model performance.
- Create a culture of ownership, collaboration, and continuous improvement, where engineers feel empowered to experiment and learn.
- Drive effective planning and delivery while balancing immediate priorities with long-term technical health.
- Foster an inclusive, supportive team environment through coaching, feedback, and thoughtful people leadership.
BASIC QUALIFICATIONS
Who You Are
- You have experience managing and developing engineering teams, with a track record of helping people grow and delivering impactful results.
- You bring a strong technical background in machine learning, software engineering, or related areas, and can confidently guide technical conversations.
- You understand the opportunities and challenges of developing and operating machine learning systems in production.
- You have experience working with cross-functional partners to define priorities, navigate trade-offs, and deliver against shared goals.
- You are comfortable leading teams through ambiguity and helping engineers make informed technical decisions.
- You care about building inclusive, collaborative environments where people feel supported and empowered.
- You communicate with clarity, lead with empathy, and know how to balance people, technology, and business needs.
LOCATION
- We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.
- This team operates within the Eastern Standard time zone for collaboration.
COMPENSATION
The United States base range for this position is $227,495 - $262,928 plus equity. 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, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
EEO STATEMENT
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.
OUR GLOBAL BENEFITS
- Extensive learning opportunities, through our dedicated team, GreenHouse.
- Flexible share incentives letting you choose how you share in our success.
- Global parental leave, six months off - for all new parents.
- All The Feels, our employee assistance program and self-care hub.
- Flexible public holidays, swap days off according to your values and beliefs.
INTRODUCTION
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.
At Spotify, great personalization is about more than recommending the right song. It's about creating listening experiences that feel effortless and meaningful while balancing the needs of listeners, creators, and our business.
The Samba team, part of Spotify's Personalization Mission, works on multi-objective balancing and sequencing for personalized listening experiences like Autoplay, Radio, and Mixes. Our engineers bring together machine learning, backend engineering, and data engineering to build systems that support Spotify's financial objectives while keeping listeners at the center of what we do.
We're looking for an Engineering Manager to lead this team, develop our engineers, and help shape the technical direction of systems that influence how millions of people experience Spotify.
ROLE AND RESPONSIBILITIES
- Lead and grow a team of machine learning, backend, and data engineers, supporting their development and helping them deliver their best work.
- Shape the team's technical strategy and execution, ensuring engineering efforts align with listener needs and Spotify's broader business goals.
- Guide the development of machine learning and recommendation systems that balance multiple objectives across personalized listening experiences.
- Collaborate with Product and engineering partners to define priorities, align on outcomes, and translate complex challenges into clear plans.
- Support the team in making thoughtful technical decisions across experimentation, scalability, system reliability, and model performance.
- Create a culture of ownership, collaboration, and continuous improvement, where engineers feel empowered to experiment and learn.
- Drive effective planning and delivery while balancing immediate priorities with long-term technical health.
- Foster an inclusive, supportive team environment through coaching, feedback, and thoughtful people leadership.
BASIC QUALIFICATIONS
Who You Are
- You have experience managing and developing engineering teams, with a track record of helping people grow and delivering impactful results.
- You bring a strong technical background in machine learning, software engineering, or related areas, and can confidently guide technical conversations.
- You understand the opportunities and challenges of developing and operating machine learning systems in production.
- You have experience working with cross-functional partners to define priorities, navigate trade-offs, and deliver against shared goals.
- You are comfortable leading teams through ambiguity and helping engineers make informed technical decisions.
- You care about building inclusive, collaborative environments where people feel supported and empowered.
- You communicate with clarity, lead with empathy, and know how to balance people, technology, and business needs.
LOCATION
- We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.
- This team operates within the Eastern Standard time zone for collaboration.
COMPENSATION
The United States base range for this position is $227,495 - $262,928 plus equity. 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, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
EEO STATEMENT
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.
OUR GLOBAL BENEFITS
- Extensive learning opportunities, through our dedicated team, GreenHouse.
- Flexible share incentives letting you choose how you share in our success.
- Global parental leave, six months off - for all new parents.
- All The Feels, our employee assistance program and self-care hub.
- Flexible public holidays, swap days off according to your values and beliefs.
See all 5,447+ Machine Learning Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Manager roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Manager
Target companies with established ML infrastructure
Large tech firms and AI-focused startups with existing ML teams are far more likely to sponsor because the business case for the role is already proven internally. Look for employers with prior H-1B LCA filings in machine learning.
Emphasize the degree-to-role connection clearly
Consular officers and USCIS adjudicators scrutinize whether your degree field directly supports the role. A computer science, statistics, or AI degree is the cleanest fit. Document how your coursework and research map to the manager's technical responsibilities.
Distinguish your leadership scope from individual contributor roles
Petitions get stronger when the role description emphasizes team oversight, research direction, and cross-functional decision-making. A generic 'ML engineer' title with added reports is weaker than a role defined by organizational and technical leadership.
Prepare for O-1A if the H-1B lottery doesn't go your way
Senior ML managers with publications, patents, conference speaking history, or industry awards may qualify for O-1A extraordinary ability status, which has no lottery and no annual cap. It's worth assessing eligibility before the next H-1B season.
Understand that prevailing wage is pegged to the senior level
Machine Learning Manager roles typically fall into Level 3 or Level 4 prevailing wage determinations under DOL guidelines. Employers must certify the offered compensation meets that threshold, which filters out underfunded early-stage startups as realistic sponsors.
Use your LCA approval as a negotiating signal
Once your employer files a certified Labor Condition Application, it confirms the role meets specialty occupation and wage standards. That certification is publicly searchable and signals market-rate commitment, giving you a stronger position in offer negotiations.
Frequently Asked Questions
Is Machine Learning Manager a qualifying specialty occupation for H-1B purposes?
Yes, in the vast majority of cases. The role requires theoretical and applied knowledge in machine learning, statistics, and software systems that directly corresponds to a specific degree field. USCIS has consistently approved H-1B visa petitions for ML leadership roles, particularly when the job description details both technical oversight and managerial scope, and the petitioner holds a bachelor's degree or higher in computer science, applied mathematics, or a closely related discipline.
Does my degree field need to be an exact match for Machine Learning Manager roles?
Not exact, but close. USCIS looks for a direct relationship between the degree field and the role's duties. Computer science, electrical engineering, applied mathematics, statistics, and AI or data science degrees are all well-established fits. A general business or unrelated humanities degree creates adjudication risk unless you can demonstrate significant coursework or a second degree in a qualifying technical field.
How competitive is H-1B sponsorship for Machine Learning Manager positions compared to other tech roles?
Machine learning roles consistently appear among the highest-volume H-1B filings in the technology sector. DOL disclosure data shows major employers filing hundreds of LCAs annually for ML-related positions. The managerial title can actually improve petition strength because it reinforces specialty occupation requirements and business necessity. The H-1B lottery remains the primary obstacle, not adjudication difficulty.
Can I find Machine Learning Manager roles that offer visa sponsorship on Migrate Mate?
Yes. Migrate Mate filters job listings specifically for roles where employers are open to visa sponsorship, saving you the time of screening out positions that exclude international candidates. Machine Learning Manager listings on Migrate Mate reflect active openings from employers with a demonstrated history of sponsoring work visas for technical leadership roles.
What happens to my H-1B status if I'm promoted from an individual contributor ML role to a manager role at the same company?
A material change in job duties, title, or work location typically requires your employer to file an amended H-1B petition before the change takes effect. Moving from an individual contributor to a managerial role qualifies as a material change under USCIS guidance. Filing an amendment is your employer's responsibility, but you should confirm it's in process before your new role begins to avoid a gap in authorized status.
What is the prevailing wage requirement for sponsored Machine Learning Manager jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.