Engineering Jobs at Spotify with Visa Sponsorship
Engineering jobs at Spotify involve building the infrastructure, algorithms, and tooling behind one of the world's most-used audio platforms. The company actively supports visa sponsorship for qualified engineers, making it a realistic target if you're on an H-1B visa or pursuing permanent residence through employment-based categories.
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Get Access To All JobsMission 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 Engineering Jobs at Spotify
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Engineering Jobs at Spotify.
Get Access To All JobsTips for Finding Engineering Jobs at Spotify
Align your resume to Spotify's engineering stack
Spotify's job postings consistently reference backend systems, distributed infrastructure, and data pipelines. Tailor your resume to reflect experience with those patterns so recruiters can quickly map your background to the open role.
Target roles that match your visa classification
Spotify sponsors both H-1B and employment-based Green Card categories. Identify which visa pathway fits your situation before applying, so you can ask the right questions about where the role falls in Spotify's immigration process.
Use Migrate Mate to surface open Engineering roles
Spotify posts Engineering roles across multiple specializations at varying times. Use Migrate Mate to browse current openings filtered by visa sponsorship eligibility, so you're applying to roles Spotify is actively hiring for.
Clarify sponsorship timing during the offer stage
H-1B cap-subject filings are tied to the April lottery window. If you receive an offer outside that window, ask Spotify's recruiting team how they handle cap-gap coverage or whether a cap-exempt pathway applies to your situation.
Prepare documentation for a specialty occupation determination
For H-1B approval, USCIS requires that both the role and your degree align as a specialty occupation. Gather transcripts, prior approval notices, and any evidence showing your degree field directly relates to the engineering position Spotify is sponsoring.
Understand how PERM affects your Green Card timeline
If Spotify pursues an EB-2 or EB-3 Green Card for you, the process starts with DOL PERM labor certification. That stage alone can take a year or more, so factor it into your long-term planning before accepting an offer.
Frequently Asked Questions
Does Spotify sponsor H-1B visas for Engineers?
Yes, Spotify sponsors H-1B visas for Engineering roles. The company works with immigration counsel to file petitions for qualified candidates. If you're cap-subject, your petition would need to go through the USCIS annual lottery, which opens in March for an October 1 start date. Roles that qualify as specialty occupations under USCIS guidelines are the ones most likely to receive sponsorship.
How do I apply for Engineering jobs at Spotify?
Applications go through Spotify's careers portal, where Engineering roles are listed by team and location. Spotify's Engineering interview process typically includes a technical screen, coding assessments, and system design rounds. Migrate Mate is a reliable way to track current openings that include visa sponsorship, so you're not wasting time applying to roles that won't support your immigration status.
Which visa types does Spotify commonly use for Engineering roles?
Spotify sponsors H-1B visas for nonimmigrant work authorization and supports employment-based Green Card categories including EB-2 and EB-3 for permanent residence. Engineers already on L-1 visa or O-1 visa status may also transfer their sponsorship to Spotify depending on the role. The right category depends on your background, degree field, and how the specific position is classified.
What qualifications does Spotify expect for sponsored Engineering roles?
Most sponsored Engineering roles at Spotify require a bachelor's degree or higher in computer science, software engineering, or a closely related field. That degree requirement isn't just a hiring preference; it's part of what establishes the role as a specialty occupation for H-1B purposes. Spotify's Engineering teams tend to look for depth in distributed systems, backend architecture, or data infrastructure depending on the specific team.
How do I think about the timeline from offer to work authorization at Spotify?
If you need a new H-1B, the timeline is largely dictated by the USCIS lottery and cap. Offers made in early spring align best with the April filing window and an October start. For transfers from another H-1B employer, Spotify can file a portability petition and you can begin work once USCIS issues a receipt notice. Green Card timelines through PERM are longer and depend on your country of birth and the DOL's processing backlog.