Original listing text, shown exactly as published by the company.
What You'll Do
- Lead end-to-end machine learning initiatives from ideation and prototyping through experimentation, deployment, and large-scale productionization.
- Design, develop, and deploy machine learning systems that operate across hundreds of millions of content signals using both real-time and batch processing architectures.
- Advance Spotify’s capabilities in natural language understanding, multimodal AI, and content intelligence.
Build and evaluate LLM-powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches.
- Define rigorous evaluation methodologies including golden datasets, precision and recall frameworks, offline benchmarking, and online experimentation.
- Partner closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy and roadmap decisions.
- Mentor engineers across the organization and help elevate machine learning engineering standards and best practices.
- Contribute to the adoption of AI-assisted development workflows and tooling that improve team productivity and engineering effectiveness.
Who You Are
- You have solid experience developing and deploying machine learning systems in production environments.
- You have successfully delivered large-scale machine learning architectures operating on substantial datasets and high-throughput production systems.
- You have deep experience with machine learning, deep learning, and modern AI technologies.
- You have hands-on experience working with large language models and understand how to evaluate, adapt, and deploy them effectively for real-world product challenges.
- You have experience building evaluation frameworks and can quantify model performance through robust experimentation and measurement techniques.
- You know how to navigate ambiguity and make thoughtful technical trade-offs that balance product impact, scalability, and engineering quality.
- You have experience influencing technical direction across cross-functional teams and can communicate complex machine learning concepts to diverse audiences.
- You care about developing others and enjoy mentoring engineers through technical guidance and collaboration.
- You have experience working with NLP, prompt engineering, retrieval-augmented generation (RAG), vector databases, or multimodal machine learning systems.
- You are curious about emerging AI technologies and excited about integrating tools such as Claude Code, Cursor, and other AI-assisted development capabilities into engineering workflows.
Where You'll Be
- This role is based in New York City
- 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.
