Job Overview
- Role: Senior Machine Learning Engineer, Personalization
- Company: Spotify
- Location: Remote
- Employment Type: Full-Time
- Category / Department: Back-End Programming
- Salary: Competitive / Not Disclosed — confirm during interview
- Listing Source: WeWorkRemotely
Job Description
Headquarters: Sweden
URL: https://newsroom.spotify.com/company-info/
You’ll join a team working at the intersection of machine learning, music understanding, and user experience. We focus on generating music sessions powering experiences like systems that power conversational playlist generation to give users more adaptive and intuitive control over what they listen to.
This team collaborates closely with product, design, user research, and data science to build personalized, high-impact features used by hundreds of millions of listeners worldwide.
What You'll Do
- Design, build, evaluate, and ship LLM-based solutions that give users more adaptive control over their listening experience
- Work on prompted playlist experiences with a focus on music fulfillment and session generation
- Collaborate with cross-functional partners across user research, design, data science, product, and engineering
- Prototype new ML approaches and bring them into production at global scale
- Build and improve systems that connect artists and fans in personalized and meaningful ways
- Contribute to the development of scalable ML systems serving hundreds of millions of users
- Promote best practices in ML system design, testing, evaluation, and deployment across the organization
- Actively contribute to a strong community of machine learning practitioners at Spotify
Who You Are
- You are experienced in machine learning and enjoy solving complex real-world problems in collaborative environments
- You have a strong background in machine learning, natural language processing, and generative AI
- You are comfortable applying theory to build real-world, production-ready applications
- You have hands-on experience building and deploying end-to-end ML systems at scale
- You are familiar with LLM-based systems and techniques for improving them using human feedback such as reinforcement fine-tuning, DPO, or similar approaches
- You have experience designing modular ML architectures and writing technical specifications in partnership with product teams
- You are experienced with large-scale distributed data processing tools such as Apache Beam or Apache Spark
- You have worked with cloud platforms like GCP or AWS
Where You'll Be
- This role is based in New York
- 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.
The United States base range for this position is $184,050 $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.
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.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
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
To apply: https://weworkremotely.com/remote-jobs/spotify-senior-machine-learning-engineer-personalization
Salary & Compensation
The salary for this role is not publicly disclosed. Based on industry benchmarks, roles of this type in India or remote-first companies typically offer compensation in line with market rates for the experience level required. We recommend researching platforms like Glassdoor, Levels.fyi, or AmbitionBox to gauge expected ranges before your offer discussion.
In addition to base salary, many employers in this sector offer a comprehensive benefits package that may include:
- Annual or performance-based bonuses
- Health, dental, and vision insurance
- Provident Fund (PF) and Gratuity contributions (India)
- Paid Time Off (PTO), sick leave, and public holidays
- Professional development budget and learning allowances
- Stock options or Employee Stock Ownership Plans (ESOPs) at select companies
- Flexible or remote working allowances
- Parental leave and family health coverage
Note: The specific benefits offered by this employer should be confirmed during the offer stage. Not all benefits listed above may apply to every organisation or role type.
Work Arrangement
Type: Fully Remote
This role is designed for a fully remote work arrangement. You will have the flexibility to work from any location, provided you have a stable internet connection and can align with the team's core collaboration hours. The company supports remote employees with the necessary tools, virtual team-building activities, and regular check-ins to ensure productivity and a strong sense of belonging. Equipment and home-office stipends may be provided — check the job listing or confirm during the offer stage.
Typical Interview Process
While each organisation structures its hiring differently, candidates for this type of role typically go through the following stages:
- Resume and application screening
- Introductory phone or video call with HR
- Role-specific skill or competency interview
- Final interview with the hiring manager or panel
- Reference checks and offer discussion
Tip: Research the company's products, culture, and recent news thoroughly before each interview round.
About the Employer
Spotify is the organisation posting this opportunity. While full company details are available on the original job listing, here is what you should research before applying:
- Company size and culture: Review the company's LinkedIn profile, Glassdoor reviews, and their official website to understand team size, work culture, and employee satisfaction.
- Products and services: Familiarise yourself with what the company builds, sells, or delivers. Being knowledgeable about their offerings will set you apart during interviews.
- Recent news: Search for any recent fundraising, acquisitions, product launches, or leadership changes — these often come up in interviews and signal company health.
- Location and offices: The role is based in or around Remote. Confirm office address, remote policy details, and travel requirements during the process.
- Where this listing was found: This job was sourced from WeWorkRemotely.
How to Apply & Preparation Tips
To apply for the Senior Machine Learning Engineer, Personalization position, follow these steps:
- Tailor your resume: Customise your CV to match the specific requirements listed in the job description. Use keywords from the posting to pass Applicant Tracking System (ATS) filters.
- Write a compelling cover letter: Even if not mandatory, a concise cover letter demonstrating your enthusiasm and fit for the role significantly improves your chances.
- Apply via the original listing: Use the apply link on the original job post to submit your application. Avoid applying through third-party channels that may delay or lose your submission.
- Prepare for phone screening: Be ready for an initial call within 3–7 business days of applying. Have your resume and a quiet space ready.
- Follow up professionally: If you haven't heard back in 7–10 business days, a brief, polite follow-up email to the recruiter is acceptable and often appreciated.
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Disclaimer: This listing is aggregated from a public job board for informational purposes. JobSetuu does not guarantee the accuracy or current availability of this position. Always verify the details on the employer's official careers page before applying.
