Spotify

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<p><span>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.</span></p>
<p><span>Growlithe is a fast-moving squad within Spotify's Conversation Product Area, focused on bringing emerging Search and agentic experiences to life. We explore, define, build, validate, and optimize new ideas to help listeners discover the content they love. Our work spans personalized Search, music video discovery and ranking, audiobook Search expansion, and the foundations of more social Search experiences.</span></p>
<p><span>We're looking for a Senior Machine Learning Engineer to help shape the next generation of Search at Spotify. You'll work at the intersection of machine learning, personalization, and product development, turning complex challenges into intuitive discovery experiences for millions of listeners.</span></p>
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<h2>What You'll Do</h2><ul><li><span>Build and improve machine learning models that make Spotify Search more relevant, personalized, and engaging for listeners.</span></li>
<li><span>Develop and optimize ranking and backend retrieval systems that help listeners discover music, videos, audiobooks, and other content.</span></li>
<li><span>Explore emerging AI and agentic approaches to create more intuitive and conversational Search experiences.</span></li>
<li><span>Design, implement, and evaluate machine learning solutions, taking ideas from early experimentation through production.</span></li>
<li><span>Partner with engineers, product managers, designers, and researchers to identify opportunities and deliver meaningful improvements to Search.</span></li>
<li><span>Use experimentation, data analysis, and performance metrics to understand model behavior, validate hypotheses, and improve the listener experience.</span></li>
<li><span>Contribute to scalable machine learning infrastructure and engineering practices that support reliable, high-quality Search experiences.</span></li>
<li><span>Share knowledge, challenge assumptions constructively, and help shape the technical direction of machine learning within the squad.</span></li></ul>
<h2>Who You Are</h2><div>

<li>You have experience building, deploying, and improving machine learning systems in production environments.</li>
<li>You have a strong understanding of machine learning approaches for information retrieval, search ranking, recommendation systems, or personalization.</li>
<li>You are proficient in Python and comfortable working with modern machine learning frameworks and data processing tools.</li>
<li>You have experience and a desire to lean into backend engineering at Spotify scale.</li>
<li>You understand how to design and evaluate experiments, interpret model performance, and translate technical findings into product improvements.</li>
<li>You have experience working with large-scale datasets and understand the challenges of building reliable, scalable machine learning systems.</li>
<li>You are curious about emerging AI technologies, including large language models and agentic systems, and interested in their potential to improve discovery experiences.</li>
<li>You enjoy working across disciplines, communicating technical ideas clearly, and learning from different perspectives.</li>
<li>You are comfortable navigating ambiguity, taking ownership of complex challenges, and balancing experimentation with practical delivery.</li>

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<h2>Where You'll Be</h2><div>

<li>This role is based in Eastern Standard Time</li>
<li>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.</li>

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Senior Machine Learning Engineer, Personalization

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<p>LilEngine is leading the Lakehouse, a company-strategic effort to make Apache Iceberg a first-class citizen in Spotify's data ecosystem. We're building it in close collaboration with Google, on open standards, so that different kinds of data are queryable the same way and teams can bring the right engine, from BigQuery to Dataflow to Trino, to the job.</p>
<p>The work has two parts. Hecate enables Iceberg for the Parquet datasets that already exist across Spotify, so teams get the benefits without rewriting their data. Alongside it, we're building the foundations of a new Lakehouse architecture that lets workflows write Iceberg tables natively. We're shipping the MVP this cycle, and you'll help shape what comes next.</p>
<p>We also own BigQuery for all of Spotify. Thousands of engineers, data scientists and pipelines depend on it every day, which puts us on the critical path for storing, finding and querying data. We're judged on reliability, cost efficiency and how quickly we unblock users when something breaks. This backend role sits where open table formats, cloud data warehouses and processing engines meet.</p>
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<h2>What You'll Do</h2><div>

<li><strong>Build and evolve the lakehouse:</strong> Help build the foundations that let data workflows read and write Iceberg tables directly, from this cycle's MVP to a production-grade platform.</li>
<li><strong>Drive adoption: </strong>Help migrate data pipelines from across Spotify onto the new stack, making the move as painless as possible through tooling, standards and hands-on support.</li>
<li><strong>Own BigQuery at Spotify scale:</strong> Manage reservations and capacity, build monitoring and anti-pattern detection, and develop tooling like the BigQuery MCP server so teams can use BigQuery well.</li>
<li><strong>Keep the platform healthy:</strong> Take part in a weekly support rotation and shared on-call. You'll debug production issues that span storage formats, catalog APIs, Kubernetes reconciliation, GCP IAM and BigQuery internals, and you'll automate away recurring toil.</li>

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<h2>Who You Are</h2><div>

<li>You have solid experience building and operating backend services in production with Java or Scala.</li>
<li>You're comfortable on GCP and Kubernetes. You can read kubectl output, reason about IAM and quotas, and work with CRDs and operators. You don't need deep expertise in all of these on day one.</li>
<li>You've worked with Apache Iceberg or JVM-based processing frameworks like Spark, Beam or Flink, or with a cloud data warehouse such as BigQuery, Snowflake or Databricks.</li>
<li>You think in systems and can connect the dots when a problem crosses several layers of the stack.</li>
<li>You like owning things in production, and you're motivated by seeing your systems run reliably for thousands of users.</li>
<li>You communicate clearly in writing and work well asynchronously across US and EU time zones.</li>
<li>You own the quality of what you ship, including code written with AI assistance.</li>

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<h2>Where You'll Be</h2><div>This role is based in London or Stockholm.</div>
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<div>We offer the flexibility to work where you work best! There will be some in person meeetings, but still allows for flexibility to work from home. </div>

Backend Engineer - Data Platform

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<p>Every dataset at Spotify, from the data behind creator royalties to the signals powering recommendations, is registered, published and traced through systems our team builds. We're the source of truth for what data exists at Spotify, where it lives, who owns it, and how it flows from one pipeline to the next.</p>
<p>These systems sit on the critical path of the platform. Data teams use them every day to publish and find data, and other platform teams build on them for access, retention, governance and incident response. That means our work is judged on correctness and reliability, because every system built on top of ours is only as good as the metadata we provide.</p>
<p>This is a backend role focused on data management, working on the problems at the core of any large data platform: running a data catalog that stays accurate at scale, capturing lineage across batch and streaming workloads, managing schemas as they evolve, and guaranteeing that consumers only read complete data. We build on open standards like OpenLineage and Apache Iceberg, and define the internal standards for naming, storage and metadata that the rest of Spotify builds against. As the platform takes on new storage technologies and new kinds of data assets, those standards and the systems behind them have to evolve with it, and you'll help decide how.</p>
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<h2>What You'll Do</h2><div>

<li>Build and Evolve Core Services: Design, build and operate the backend services and APIs behind our data catalog, lineage and publishing systems, and evolve them as the platform adopts new storage technologies and new kinds of data. Hold them to a high bar for correctness, performance and reliability.</li>
<li>Build Data Pipelines: Develop and run the batch and streaming pipelines that keep our metadata current, processing platform events and audit logs to capture how data is created and changed, and turning lineage and metadata into data products other teams build on.</li>
<li>Own Projects End to End: Turn what the teams using our platform need into technical designs, drive them through delivery and rollout, and own the results once they're in production.</li>
<li>Keep the Platform Healthy: Take part in on-call for critical services, build in observability and quality checks by default, and use automation, including AI tooling, to reduce toil for the team and our users.</li>

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<h2>Who You Are</h2><div>

<li>You have solid experience building and running backend services and APIs in production with Java, and you care about API design, versioning and backward compatibility.</li>
<li>You're comfortable with SQL and have worked with data pipelines or a cloud data warehouse such as BigQuery, Snowflake or Databricks. Hands-on experience with batch or streaming frameworks like Beam, Flink or Spark is a plus.</li>
<li>You have a working understanding of data engineering concepts such as orchestration, metadata management, data quality, governance and lineage.</li>
<li>You break problems down into clear, shippable steps, reasoning through tradeoffs and risks and converging on clear recommendations.</li>
<li>You own the quality of what you ship, including code written with AI assistance, and you care about operating it well after launch.</li>
<li>You are a strong communicator and collaborator who enjoys working across teams, and you're comfortable in a dynamic platform environment where many engineers depend on what you build and priorities evolve with the business.</li>

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<h2>Where You'll Be</h2><ul><li>This role is based in Stockholm or London.</li>
<li>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. </li></ul>

Backend Engineer II - Data Platform

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<p>The Experience team designs Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.</p>
<p>The Content Intelligence Product Area is a core part of Spotify’s Content Platform within the Experience mission. We build systems that create deep, machine-readable understanding of content across audio, video, text, and images before it reaches users. This enables automation, safety, and entirely new product experiences. Our work powers content enrichment, quality analysis, annotation platforms, and scalable intelligence systems that allow teams across Spotify to build without needing direct content understanding expertise.</p>
<p>We’re looking for a Senior Backend Data Engineer to help build and scale the systems powering content understanding across Spotify. This role sits at the intersection of backend engineering, distributed data systems, ML infrastructure, and applied AI. You’ll take end-to-end ownership of significant engineering problems while working alongside other Engineers.</p>
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<h2>What You Will Do</h2><div>

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<p>Design, build, and evolve scalable backend and data systems powering Spotify’s content intelligence capabilities</p>
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<p>Take end-to-end ownership of significant engineering projects, from technical design and architecture through implementation and operation</p>
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<p>Build reliable infrastructure for large-scale content processing across audio, video, text, and images</p>
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<p>Create RFCs and contribute to architectural decisions within your squad and across connected systems</p>
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<p>Develop reliable and cost-efficient systems for high-throughput data and content-processing workloads</p>
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<p>Work with distributed data systems and large-scale content-management infrastructure</p>
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<p>Partner closely with other Engineers to plan and deliver technical solutions</p>
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<p>Contribute to AI and LLM-enabled workflows and infrastructure, including systems for content understanding, enrichment, and processing</p>
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<p>Evaluate and integrate AI capabilities into production systems at scale</p>
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<p>Build a strong understanding of adjacent systems and contribute to a shared on-call rotation</p>
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<p>Contribute to technical quality and engineering best practices across the team</p>
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<h2>Who You Are</h2><div>

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<p>You have 5+ years of relevant engineering experience, with strong experience in backend and/or data engineering</p>
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<p>You have deep expertise in either backend or data engineering and are comfortable working across both disciplines</p>
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<p>You have experience building and scaling large-scale distributed systems</p>
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<p>You have strong programming experience in Java, Scala, and/or Python</p>
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<p>You understand how to design systems with scalability, reliability, performance, and cost in mind</p>
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<p>You’re comfortable taking end-to-end ownership of complex engineering problems</p>
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<p>You can translate technical problems into designs, RFCs, and executable engineering plans</p>
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<p>You communicate effectively and enjoy collaborating with engineering, product, and technical stakeholders</p>
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<p>You’re comfortable operating in an environment where backend, data, ML infrastructure, and AI increasingly overlap</p>
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<p>You’re able to participate in a shared on-call rotation</p>
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<p>Experience with ML infrastructure, AI/LLM systems, agents, model evaluation, or integrating model APIs at scale is a plus</p>
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<p>Exposure to large-scale multimedia processing, audio processing, search, or recommendation systems is a plus</p>
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<h2>Where You’ll Be</h2><div>

<li>
<p>This role is based in London or Stockholm</p>
</li>
<li>
<p>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.</p>
</li>

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Senior Backend Data Engineer – Content Intelligence

<div>
<div>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.</div>
<div><br />Within Personalization, the Speak Team owns the development of Spotify's state-of-the-art speech models, contributing to speech recognition, speech synthesis, and speech-to-speech models. We craft voice models that match human-level emotional expressiveness, so we can deeply engage our listeners and support creators at scale. Our groundbreaking work on speech synthesis relies on state-of-the-art deep learning methods and evaluation techniques, highly efficient data processing and model serving, and capturing audio of outstanding quality from our voice talent pool.</div>
<div><br />We're looking for a senior applied research scientist with experience in developing novel ML techniques and architectures and with a strong interest in working across a full production pipeline to produce state-of-the-art generative conversational speech-to-speech models. You'll collaborate with our engineering teams to help develop our production pipelines, explore new ideas and methods to improve quality, understanding and realism, as well as push the frontiers of what is possible with our speech technology.</div>
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<h2>What You'll Do</h2><div>
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<li>Develop and experiment with new methods for speech synthesis and speech recognition, along with end-to-end approaches, building on the latest research and ideas.</li>
<li>Work towards the expansion of our speech use-cases targeting different markets and products.</li>
<li>Be part of a highly motivated research team dedicated to building and creating models at scale to power the Spotify platform.</li>
<li>Champion best practices for research and development, sharing your knowledge and experience with other researchers within Speak.</li>
<li>Collaborate with our engineering and data teams on ideas requiring new infrastructure or new high-quality data, as well as to help improve our speech recognition and speech synthesis pipelines, and help turn proven ideas into scalable products.</li>

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<h2>Who You Are</h2><div>
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<li>You have a strong background in ML (PhD degree on top of professional experience), and experience in working with any of the following: transformers, GANs, diffusion models, flow matching, VAEs, audio codecs.</li>
<li>You have experience in developing generative models for speech synthesis, speech recognition, audio/music, natural language processing, or computer vision.</li>
<li>You have strong experience with Python, particularly PyTorch.</li>
<li>You have strong communication skills and the ability to explain technical ideas with clarity to technical and non-technical people alike.</li>
<li>You have experience in an academic or professional setting conducting high-quality research.</li>

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<h2>Where You'll Be</h2><div>
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<li>This role is based in London or Stockholm.</li>
<li>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</li>

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Spotify

Open jobs at Spotify

Senior Machine Learning Engineer, Personalization

Backend Engineer - Data Platform

Backend Engineer II - Data Platform

Senior Backend Data Engineer – Content Intelligence

Senior Applied Research Scientist - Personalization

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