• Own the end-to-end technical roadmap for the A&R and Fan Insights platforms. You will design scalable, secure systems capable of handling massive datasets with high performance.
• Act as the technical lead for a small, expert squad. You will lead by example through architectural clarity, rigorous peer reviews, and a focus on maintaining high execution momentum.
• Work as a peer to Product Managers and Designers to define requirements. You’ll turn vague business "wants" into concrete technical "hows," ensuring the team builds the right things in the most efficient way.
• Ensure high technical standards across both Frontend and Data disciplines. While the team is highly capable, you are responsible for the overall technical health, consistency, and long-term sustainability of the codebase.
• We operate with an AI-agentic mindset. You will champion "AI-native" development – leveraging modern agentic tools (like Cursor or Claude Code) to multiply the team's impact and identifying high-value opportunities to deploy agentic capabilities directly to our users.
• Own the infrastructure and health of your domain. You’ll manage deployment patterns, infrastructure as code (Terraform), and ensure we adhere to modern security standards.
• Leverage agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods. 

• You have a track record of architecting and scaling robust backend systems and high-performance services. You are a generalist who can navigate complex application logic or resolve infrastructure bottlenecks with equal ease.
• The Stack:
  • Backend: Proficiency in Scala or Golang for building reliable services and a strong understanding of handling storage and querying of BigData (e.g., BigQuery, SQL).
  • Frontend: Comfort with Next.js and React—enough to drive architectural decisions and ensure best practices.
  • Infrastructure: Experience with Infrastructure as Code (Terraform) and container orchestration.
• Soft Skills & Leadership: You behave as a leader naturally. You can explain complex technical trade-offs to non-technical stakeholders and have the ambition to grow into a formal management role.
• You use modern agentic tools daily to accelerate your own work and are excited about the future of agentic software.
• Bonus Points
  • Experience with AWS ECS.
  • Experience with Python and data orchestration via Airflow.
  • Experience with Google Cloud Platform (GCP).
  • Experience with large-scale data warehouses like BigQuery.

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)

• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home

• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.

• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival

• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!

• Employee Equity Plan

• Generous professional development allowance

• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually

• Various snacks, goodies, and 2 free lunches weekly when at the office

The salary range for this role is $165,000 - $195,000 annually. The final salary offered will be determined based on relative experience, skills, internal equity, and location. We also offer a generous total rewards program - read more about additional benefits and perks below!

Key Responsibilities: 

• Develop, test, and productionize ML and LLM-based systems serving real users
• Design and build end-to-end ML pipelines, including data, features, training, and serving
• Make technical decisions considering cost, latency, complexity, and maintainability 
• Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to build reliable, scalable solutions
• Set up monitoring, A/B testing, and metrics frameworks to measure real user impact
• Debug complex issues across data pipelines, ML models, and distributed systems
• Contribute to technical strategy and team best practices
• Leverage agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods

Experience and Background:

• 1-2+ years building ML systems in production - you understand the difference between a model that works in Jupyter and one that serves millions of users
• 4+ years of software engineering experience - you write production code, not just notebooks
• Strong Python and Scala (or Java/JVM) skills, with experience writing scalable, production code
• Experience building and deploying ML models end-to-end (data, training, serving, monitoring)
• Experience building and deploying LLM-based features in production
• Familiarity with integrating LLMs into ML systems (e.g. retrieval-augmented generation, model serving)
• Understanding of shared ML architecture across domains (e.g. search and recommendations)
• Strong focus on data quality and correctness, and how upstream data impacts downstream models and user experience
• Strong SQL skills for massive datasets (BigQuery, Spark)
• Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes)
• Experience with distributed data processing and ETL pipelines (Airflow, Spark)
• Familiarity with ML frameworks such as TensorFlow or PyTorch