Spotify

Engineering Manager

• Lead the technical direction for subscription management systems across backend, web, and mobile surfaces
• Be accountable for delivery outcomes, system health, and operational reliability at scale
• Shape the Account Management subdomain strategy and bring clarity to ownership boundaries across teams
• Drive architectural simplification to improve scalability, maintainability, and developer experience
• Influence technical direction across the Freemium Funnel domain through strong cross-team collaboration
• Build and grow a high-performing engineering team grounded in accountability, ownership, and continuous improvement
• Balance short-term delivery with long-term platform sustainability and evolution

Engineering Manager – Subscriptions

Machine Learning Engineer

• Lead and support engineering managers and their teams building platform systems for personalized recommendations across Spotify
• Set and evolve the technical vision for foundational capabilities, including targeting, serving, evaluation, and agent-driven systems
• Make thoughtful decisions about what should become platform capabilities, ensuring teams can move quickly without unnecessary complexity
• Guide incremental platform evolution, enabling continuous delivery rather than large, disruptive rewrites
• Partner closely with product, data science, and engineering leaders to align priorities across multiple squads
• Stay close to the technology when needed, contributing to architecture decisions and resolving complex production challenges
• Encourage adoption of AI-assisted development tools and shape how teams use them effectively in day-to-day work
• Hire, develop, and grow engineering leaders and individual contributors, building a strong and inclusive team culture

Director, Machine Learning Engineering – Surfaces Foundation

• Lead and support a team of research engineers and machine learning engineers, helping them grow and do their best work
• Define and deliver the engineering roadmap, balancing fast experimentation with production readiness
• Build and scale machine learning infrastructure, including training pipelines, experimentation systems, and shared tooling
• Partner with research scientists, product managers, and platform teams to bring ideas from research into user-facing features
• Improve engineering practices in a research environment, including testing, reproducibility, and deployment workflows
• Support the transition of research prototypes into reliable, scalable production systems
• Contribute to strategic planning and align engineering work with broader company priorities

Machine Learning Engineering Manager – Music

Producer

• Lead and support a team of two producers, guiding day-to-day execution across multiple audiobook productions
• Oversee end-to-end production, from pre-production, casting, recording, quality control, and delivery
• Set clear project scopes, timelines, and deliverables, identifying risks early and keeping projects on track
• Collaborate with internal teams and external partners to ensure alignment on creative vision and production goals
• Act as the primary production partner to Publishing, aligning output with partner commitments and content priorities
• Work closely with Partner Relations and Content Strategy to translate business needs into strong production plans
• Manage budgets, contracts, and vendor relationships, ensuring smooth delivery from scoping through wrap
• Lead casting decisions and direct recording sessions, ensuring each title meets a high creative standard
• Build and maintain relationships with narrators and production partners to support a diverse and scalable talent network
• Help improve and standardize production workflows to support a growing catalog of audiobook content

Lead Producer, Audiobook Production

Frontend Engineer

• Build and evolve the Spotify Rights Center web application used by music labels, publishers, and other rightsholders to manage how their content appears on Spotify
• Collaborate closely with product managers, designers, and backend engineers to deliver intuitive and high-quality user experiences
• Develop complex workflows that support large datasets, territory-level permissions, and multi-step processes for managing rights and disputes
• Integrate frontend systems with multiple backend services to support scalable and reliable data flows
• Write performant, accessible, and well-tested frontend code using modern development practices
• Partner with backend engineers to design and evolve APIs that support the needs of the product
• Contribute to product discovery and ideation with engineers, researchers, and product specialists
• Help improve engineering practices and advocate for strong frontend architecture and quality standards
• Support a collaborative team environment that encourages learning, experimentation, and growth

Frontend Engineer – Music

QA Engineer

• Review annotated data to ensure it meets Spotify’s quality standards and policies, prioritizing work based on business needs
• Deliver high-quality, timely results for Product and Engineering teams using established QA frameworks and metrics such as agreement rates and consensus
• Handle complex edge cases, helping define ground truth and reduce ambiguity across datasets
• Identify patterns, insights, and areas for improvement, and communicate findings clearly to both technical and non-technical partners
• Contribute to feedback loops between annotation teams, R&D collaborators, and content policy experts to improve workflows and outputs
• Help develop and refine annotation guidelines, supporting annotator training and continuous improvement
• Collaborate closely with teammates across multiple projects and domains

Annotation QA Analyst – Content Platform

• Define & drive machine learning strategy for safety, policy enforcement, and compliance systems
• Build and scale ML systems for detection, classification, and risk assessment across content
• Develop automated decisioning systems that ensure consistent, reliable enforcement of policies
• Design systems that support real-time and large-scale content evaluation
• Collaborate with product, policy, and trust & safety teams to operationalize content standards
• Improve automation to reduce manual intervention, maintaining high quality and safety standards
• Drive best practices in evaluation, fairness, and system reliability
• Mentor engineers and contribute to technical direction across teams

Senior Staff Machine Learning Engineer – Content Policy & Safety

• Shape the machine learning direction for UI Studio as it evolves into a generative UI platform
• Build systems that translate natural language into fully functional UI experiences through applied agent chat
• Design and implement agent-based architectures (e.g., Claude Agent SDK or similar) as the core interaction layer for UI generation
• Lead work on computational understanding of UI — transforming design files, product specs, and prompts into structured, machine-readable representations
• Develop pipelines that convert unstructured inputs (e.g., Figma files, free-form prompts, internal data) into structured UI blueprints
• Apply ML techniques to generate, interpret, and manipulate visual interface structures at scale
• Partner closely with design and product to bridge the gap between human intent and generated UI output
• Help integrate an evaluation framework into the application to help guide our system to produce better results
• Contribute to evolving the ML and agent tech stack across TypeScript and Python environments
• Help scale the platform from early adoption into a foundational capability used across Spotify

Senior Machine Learning Engineer – Generative UI Platform

• lead and grow a team of engineers building large-scale systems that power content delivery across Spotify
• set technical direction and guide the evolution of backend systems for content distribution
• partner closely with product, design, and platform teams for reliable, high-impact solutions
• ensure highly available, scalable, and performant infrastructure supporting millions of content interactions
• foster a culture of ownership, collaboration, and continuous improvement within the team
• support engineers through coaching, feedback, and career development
• drive execution across complex, cross-functional initiatives involving multiple systems and stakeholders
• champion best practices in reliability, observability, and system design

Engineering Manager – Content Platform

• lead the end-to-end delivery of complex engineering initiatives
• partner closely with Product and Design to shape a technically sound roadmap
• support your team in delivering high-impact work
• empower engineers to communicate technical decisions
• foster a strong team culture through regular 1:1s and feedback
• guide architectural discussions, balancing needs with system quality
• evaluate trade-offs across technical investments
• use data and metrics to inform decisions
• model and encourage thoughtful use of AI

Engineering Manager II – Creator and Publisher Analytics

Sales

• Set and drive the growth strategy for the E&S business across Southern Europe, sharing market insights with your team
• Lead, coach, and develop a team of Client Partners across France, Italy, and Spain
• Define and scale a new business strategy, building a consistent and effective prospecting approach
• Partner with SDR resources to strengthen pipeline generation and improve lead flow
• Build and maintain strong relationships with key clients and agency partners
• Support high-impact pitches, negotiations, and renewals for strategic accounts
• Identify opportunities to grow advertiser investment and support Client Partners in expanding accounts
• Encourage adoption of Spotify Ads Manager and performance-led, multi-format campaigns
• Use measurement frameworks and KPIs to demonstrate impact and guide decisions
• Partner with Sales Operations to set quotas and optimize account allocation
• Stay up to date on Spotify’s advertising products and identify opportunities for growth
• Analyze market trends to identify and prioritize new opportunities
• Collaborate cross-functionally with Sales Ops, Product, Marketing, and Measurement teams
• Represent Spotify at industry events across Southern Europe
• Foster a collaborative team culture by sharing knowledge and best practices
• Manage pipeline, forecasts, and sales activity using Salesforce

Director of Sales, Emerging & Scaled

Data Scientist

• Act as a key partner to leaders in Spotify’s Music Vertical
• Manage a strong team of data scientists
• Conduct research and craft compelling data storytelling
• Orient innovation at the intersection of human editorial and algorithmic recommendations
• Upskill the data science function with agentic AI
• Develop self-serve access to insights for stakeholders
• Become a company-wide expert on music content

Data Science Manager, Music Recommendations

Software Engineer

• Lead and develop multiple engineering teams through engineering managers, supporting their growth and impact
• Own and drive the technical strategy for a critical platform domain, aligning with broader company and platform goals
• Enable teams across Spotify to build product experiences efficiently by improving the underlying catalog systems
• Guide the evolution and modernization of complex, legacy systems into scalable, reliable architecture
• Partner closely with product and cross-functional leaders to align priorities and drive execution
• Improve system reliability and reduce operational friction in workflows that directly impact content availability
• Identify and apply opportunities for automation and AI to improve data quality and engineering productivity
• Build a strong, inclusive engineering culture where teams continuously improve how they work and deliver
• Develop and execute a long-term roadmap balancing immediate priorities with strategic investments

Director of Engineering – Experience

• Build and lead a robust team of data and backend engineers by attracting top talent, mentoring individuals and managing conflict.
• Work with product managers and lead the team to design and implement product features, while improving the quality of the current big-data intensive tools that exist for audiences and targeting.
• Lead the team to utilize, homogenize and make available for peer teams to use, diverse large-volume datasets built around user preferences, behavior, identity and location - gathered from a user's mobile as well as other connected platforms.
• Strong understanding of how data-intensive systems are expressed in the UX shown to customers.
• Grow the technical expertise of the team around system design, quality and testing, scalability, performance and fault tolerance.
• Manage OKRs, roadmaps, career conversations, performance and accountability, and thereby carefully plan, track, and report on work of the team and identify problems early.
• Work closely with many peer teams to ensure that our systems are designed in a scalable and maintainable manner.
• Nurture a culture of technical quality from design, through code review, to production.
• Drive optimization, testing and tooling to improve data quality.

Engineering Manager – Subscriptions

Director, Machine Learning Engineering – Surfaces Foundation

Machine Learning Engineering Manager – Music

Lead Producer, Audiobook Production

Director, Machine Learning Engineering – Surfaces Foundation

Frontend Engineer – Music

Annotation QA Analyst – Content Platform

Senior Staff Machine Learning Engineer – Content Policy & Safety

Senior Machine Learning Engineer – Generative UI Platform

Engineering Manager – Content Platform

Engineering Manager II – Creator and Publisher Analytics

Director of Sales, Emerging & Scaled

Data Science Manager, Music Recommendations

Director of Engineering – Experience

Engineering Manager – Advertising