[Remote] Staff Machine Learning Engineer, Home Surfaces

Note: The job is a remote job and is open to candidates in USA. Spotify’s Surfaces Podcasts team builds podcast recommendations across prominent surfaces, including Home and Now Playing. The Staff Machine Learning Engineer will develop and productionize personalized discovery systems, apply large language models, and help set technical direction for personalization at scale.

Responsibilities

• Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience
• Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally
• Build content recommendation systems for emerging agentic and AI-powered user experiences
• Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches
• Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies
• Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency
• Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale
• Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of our personalization systems
• Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team

Skills

• You have deep experience building and deploying machine learning systems in production environments
• You have deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms
• You are proficient in Python and have hands-on experience building machine learning systems with PyTorch
• You have experience with large language model training, fine-tuning, evaluation, and optimization techniques, including SFT, distillation, and LoRA
• You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization
• You care about creating high-quality user experiences through thoughtful applications of machine learning
• You communicate effectively with technical and non-technical partners and can influence technical decisions beyond your immediate team
• You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes
• You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks
• You have experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms

Benefits

• Equity
• Health insurance
• Six month paid parental leave
• 401(k) retirement plan
• Monthly meal allowance
• 23 paid days off
• 13 paid flexible holidays
• Paid sick leave
• Flexible work location within the North Americas region, provided Spotify has a work location there

Company Overview

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