Spotify

<div>We are looking for a Data Scientist to join the Finance Data &amp; Insights organization. You will support the Legal and Finance organizations through data analytics and ad-hoc reporting, while using your experience to improve data self-service capabilities and automation through AI tooling. You will also contribute to process automation and provide technical and data guidance to Legal and Finance partners.</div>
<h2>What You'll Do</h2><div>

<li>Gain and apply a deep understanding of Spotify’s data ecosystem to support operational data requirements for legal requests</li>
<li>Work with a cross-functional team of data scientists, engineers, and functional stakeholders to develop and maintain systems and processes that support Legal and Finance</li>
<li>Partner with engineering teams to gather requirements and generate outputs for technically complex matters</li>
<li>Work with large datasets to solve complex problems in a fast-paced and dynamic environment</li>
<li>Improve process efficiency through automation and the delivery of data pipelines that strengthen existing self-service reporting and analytics</li>
<li>Collaborate with highly motivated colleagues who are passionate about Spotify’s success</li>

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

<li>You have a passion for solving complex problems through data analysis, combined with strong business acumen and excellent communication skills</li>
<li>You can communicate effectively with both technical and non-technical teams to understand problems and articulate proposed solutions</li>
<li>You can draw meaningful conclusions from analysis and investigations that inform business decisions</li>
<li>You have experience validating datasets and outputs created by other teams or members of your team</li>
<li>You can identify opportunities to make processes more efficient and translate common workflows into feature requirements</li>
<li>You have 4+ years of experience in data analytics, including relevant experience with financial and/or legal data</li>
<li>You have a degree in information systems, computer science, finance, mathematics, or another quantitative discipline</li>
<li>You have experience performing analysis across large and complex datasets</li>
<li>You have strong SQL knowledge and experience using Claude Code, Codex, or other AI platforms for research, routines, and text-to-SQL capabilities</li>

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

<li>This role is based in New York.</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>
<li>We ask that you come in 2–3 times per week.</li>

</div>

Data Scientist, Finance Data & Insights

<div>
<p>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.</p>
<p>Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.</p>
<p>As a Senior Machine Learning Engineer, you will help shape the future of personalized discovery and engagement at Spotify. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, collaborating across disciplines, and solving complex personalization challenges at global scale.</p>
</div>
<h2>What You'll Do</h2><ul><li>Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.</li>
<li>Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally.</li>
<li>Build content recommendation systems for emerging agentic and AI-powered user experiences.</li>
<li>Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches.</li>
<li>Partner closely with product managers, engineers, data scientists, and designers to define and execute experimentation strategies.</li>
<li>Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.</li>
<li>Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.</li></ul>
<h2>Who You Are</h2><ul><li>You have 5+ years of experience building and deploying machine learning systems in production environments.</li>
<li>You have deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.</li>
<li>You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.</li>
<li>You are experienced with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA.</li>
<li>You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization.</li>
<li>You care deeply about creating high-quality user experiences through thoughtful application of machine learning.</li>
<li>You communicate effectively across technical and non-technical audiences and enjoy working in highly collaborative environments.</li>
<li>You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.</li>
<li>You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.</li>
<li>You are experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.</li></ul>
<h2>Where You'll Be</h2><div>

<li>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.</li>
<li>This team operates within the Eastern Standard time zone for collaboration.</li>

</div>

Senior Machine Learning Engineer, Surfaces Moments

<div>
<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 Enrichment &amp; Content Intelligence team sits within Content Platform in the Experience Mission. We build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale. Our systems help answer foundational questions across the platform: which tracks are the same recording, which music videos match which audio tracks, who wrote and performed a song, and how content relationships connect across Spotify’s catalog.</p>
<p>Our infrastructure powers products and experiences used by millions of listeners, artists, and creators every day. From recommendations and charts to royalties and artist tooling, the work we do directly shapes how content is understood and surfaced across Spotify.</p>
<p>We’re looking for a Senior Machine Learning Engineer to help evolve the machine learning systems behind Recording Groups, Music Video Resolution, SongDNA, and the Music Knowledge Graph. This role sits at the intersection of multimodal machine learning, entity resolution, and production-scale engineering, with opportunities to work across audio, video, and metadata understanding problems at massive scale.</p>
</div>
<h2>What You'll Do</h2><div>

<li>Own and evolve large-scale ML pipelines powering Spotify’s content-resolution systems</li>
<li>Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA</li>
<li>Improve entity-resolution systems across music and video content, helping Spotify better understand relationships between recordings, versions, and content formats</li>
<li>Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis</li>
<li>Build scalable ML evaluation and monitoring infrastructure, including standardized datasets, retraining workflows, and continuous improvement systems</li>
<li>Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management</li>
<li>Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission</li>
<li>Help shape technical strategy for the squad and contribute to long-term ML direction across the product area</li>
<li>Mentor engineers and contribute to a strong culture of technical collaboration and experimentation</li>

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

<li>You have solid experience building, deploying, and maintaining machine learning systems in production at scale</li>
<li>You have strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow</li>
<li>You have experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains</li>
<li>You understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities</li>
<li>You know how to design evaluation systems that balance model quality, operational performance, and real-world impact</li>
<li>You are experienced working with large-scale distributed data processing systems and ML infrastructure</li>
<li>You communicate effectively across engineering, product, and data science stakeholders</li>
<li>You are comfortable leading technical initiatives and influencing engineering direction within a team</li>
<li>Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks is a plus</li>
<li>Experience with Scala is a plus</li>
<li>Experience with computer vision, video understanding, multimodal embeddings, or recommendation systems is a strong plus</li>

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

<li>This role is based in New York City</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>

</div>

Senior Machine Learning Engineer - Enrichment & Content Intelligence

<div>
<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 now looking for a Staff Engineer to help build and scale foundational infrastructure powering content understanding across Spotify. This role sits at the intersection of backend systems, ML infrastructure, distributed data systems, and AI-enabled platform capabilities. You’ll help shape infrastructure strategy across the product area while partnering with senior engineers, product leaders, and cross-functional teams to execute on long-term technical investments.</p>
</div>
<h2>What You'll Do</h2><div>

<li>
<p>Lead the design and evolution of data, backend and ML infrastructure systems powering Spotify’s content intelligence capabilities</p>
</li>
<li>
<p>Build scalable infrastructure for multimodal content processing across audio, video, text, and image understanding pipelines</p>
</li>
<li>
<p>Partner closely with Product Managers, Engineering Managers, and senior engineers to shape technical strategy across the Content Intelligence Product Area</p>
</li>
<li>
<p>Drive architectural decisions across distributed systems, ML infrastructure, data processing platforms, and platform reliability</p>
</li>
<li>
<p>Improve infrastructure supporting AI and LLM-enabled workflows, including podcast and audiobook transcript processing, metadata enrichment, and content understanding systems</p>
</li>
<li>
<p>Develop reliable and cost-efficient systems for high-throughput content processing and real-time intelligence use cases</p>
</li>
<li>
<p>Collaborate across organizational boundaries to drive alignment, technical quality, and long-term platform investments</p>
</li>
<li>
<p>Mentor engineers and contribute to raising the engineering bar across the organization</p>
</li>

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

<li>
<p>You have extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments</p>
</li>
<li>
<p>You have strong technical judgment and can balance scalability, reliability, cost, and product needs effectively</p>
</li>
<li>
<p>You have strong programming experience in Java, Python, and/or Scala</p>
</li>
<li>
<p>You understand the challenges of building systems that process high-volume multimedia or real-time workloads</p>
</li>
<li>
<p>You have worked with systems and products that use AI and LLMs at large scale and can demonstrate direct experience in building such products. You can demonstrate a good understanding of the quality scale and cost trade-offs of these technologies.</p>
</li>
<li>
<p>You are comfortable operating in ambiguous, fast-moving environments and helping shape technical direction from the ground up</p>
</li>
<li>
<p>You communicate effectively across engineering, product, and leadership stakeholders</p>
</li>
<li>
<p>You have experience leading complex technical initiatives that span multiple teams or organizational areas</p>
</li>
<li>
<p>You care deeply about collaboration, mentorship, and creating alignment across teams</p>
</li>
<li>
<p>Exposure to search infrastructure, recommendation systems, or audio processing systems is a strong plus</p>
</li>
<li>
<p>Experience working in startup environments or early-stage product areas where ownership and adaptability are critical is highly valued</p>
</li>

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

<li>
<p>This role is based in New York</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>

</div>

Staff Engineer - Content Intelligence Infrastructure

<div>
<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 now looking for a Staff Engineer to help build and scale foundational infrastructure powering content understanding across Spotify. This role sits at the intersection of backend systems, ML infrastructure, distributed data systems, and AI-enabled platform capabilities. You’ll help shape infrastructure strategy across the product area while partnering with senior engineers, product leaders, and cross-functional teams to execute on long-term technical investments.</p>
</div>
<h2>What You'll Do</h2><div>

<li>
<p>Lead the design and evolution of data, backend and ML infrastructure systems powering Spotify’s content intelligence capabilities</p>
</li>
<li>
<p>Build scalable infrastructure for multimodal content processing across audio, video, text, and image understanding pipelines</p>
</li>
<li>
<p>Partner closely with Product Managers, Engineering Managers, and senior engineers to shape technical strategy across the Content Intelligence Product Area</p>
</li>
<li>
<p>Drive architectural decisions across distributed systems, ML infrastructure, data processing platforms, and platform reliability</p>
</li>
<li>
<p>Improve infrastructure supporting AI and LLM-enabled workflows, including podcast and audiobook transcript processing, metadata enrichment, and content understanding systems</p>
</li>
<li>
<p>Develop reliable and cost-efficient systems for high-throughput content processing and real-time intelligence use cases</p>
</li>
<li>
<p>Collaborate across organizational boundaries to drive alignment, technical quality, and long-term platform investments</p>
</li>
<li>
<p>Mentor engineers and contribute to raising the engineering bar across the organization</p>
</li>

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

<li>
<p>You have extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments</p>
</li>
<li>
<p>You have strong technical judgment and can balance scalability, reliability, cost, and product needs effectively</p>
</li>
<li>
<p>You have strong programming experience in Java, Python, and/or Scala</p>
</li>
<li>
<p>You understand the challenges of building systems that process high-volume multimedia or real-time workloads</p>
</li>
<li>
<p>You have worked with systems and products that use AI and LLMs at large scale and can demonstrate direct experience in building such products. You can demonstrate a good understanding of the quality scale and cost trade-offs of these technologies.</p>
</li>
<li>
<p>You are comfortable operating in ambiguous, fast-moving environments and helping shape technical direction from the ground up</p>
</li>
<li>
<p>You communicate effectively across engineering, product, and leadership stakeholders</p>
</li>
<li>
<p>You have experience leading complex technical initiatives that span multiple teams or organizational areas</p>
</li>
<li>
<p>You care deeply about collaboration, mentorship, and creating alignment across teams</p>
</li>
<li>
<p>Exposure to search infrastructure, recommendation systems, or audio processing systems is a strong plus</p>
</li>
<li>
<p>Experience working in startup environments or early-stage product areas where ownership and adaptability are critical is highly valued</p>
</li>

</div>
<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>

</div>

Spotify

Open jobs at Spotify

Data Scientist, Finance Data & Insights

Senior Machine Learning Engineer, Surfaces Moments

Senior Machine Learning Engineer - Enrichment & Content Intelligence

Staff Engineer - Content Intelligence Infrastructure

Staff Engineer - Content Intelligence Infrastructure

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