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Professional Services • Software
The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.
Top Skills:
AzureBayesian NetworksCi/CdConstraint ProgrammingDbtDockerKubernetesMachine LearningMonte CarloReinforcement LearningSnowflake
Other • Real Estate • PropTech
As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.
Top Skills:
LangchainLanggraphPythonPyTorchTensorFlow
AdTech • Digital Media • eCommerce • Marketing Tech • Mobile • Software
The Senior Machine Learning Engineer will manage the full ML lifecycle, collaborating with teams to develop scalable systems that improve product decisions and empower monetization strategies.
Top Skills:
AirflowAWSDbtPythonPyTorchRedisScikit-LearnSparkSQLTensorFlow
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.
Prompted Playlists (P2P) let listeners describe exactly what they want to hear and set the rules for their personalized playlist experience. This feature taps into a listener’s entire Spotify history—stretching back to day one—to reflect not just what they love now, but the full arc of their taste. The team blends personalization, world knowledge, and adaptive curation to deliver playlists that stay fresh, relevant, and delightful. P2P is looking for an experienced ML engineer to join the team!
What You'll Do
- Design, build, evaluate, and ship LLM based solutions that will enable our users to have more adaptive control of their content
- Collaborate with cross functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways
- Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
- Be part of an active group of machine learning practitioners
Who You Are
- An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment -
- Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications
- Hands-on expertise with implementing end-to-end production ML systems at scale. Experience with production LLM scale based systems is a plus
- Experience with incorporating human feedback to improve LLM based systems using technicals like DPO, KTO, and reinforcement fine-tuning
- Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
- Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS
Where You'll Be
- 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.
The United States base range for this position is $125,300 - $179,000 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. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. 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.
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
