Hiring: Staff Machine Learning Engineer, Home Surfaces Company: Spotify Location: New York, NY Job Posted Time: 2026-09-11 17:56:38 Employment Type: Full-time Target Skills & Keywords: Machine Learning, Recommendation Systems, Personalization, Large Language Models (LLMs), Ranking Models, PyTorch, Python, SFT, Distillation, LoRA, A/B Testing, Distributed Training, Ray, FSDP, HSDP, Flyte, Airflow, BigQuery, Data Pipelines, Inference Systems, Content Discovery Experience: - 8+ years of experience building and deploying machine learning systems in production environments - Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms - Experience with large-scale inference systems and understanding of latency, reliability, and cost optimization challenges - Experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks - Experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms Required Skills: - Strong proficiency in Python - Hands-on experience building machine learning systems with PyTorch - Large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA - Designing, executing, and interpreting online experiments and A/B tests - Driving technical direction in ambiguous problem spaces - Effective communication across technical and non-technical audiences - Mentoring and supporting other machine learning engineers Qualifications: - Ability to own and improve ML models and systems powering the Home feed, including the Shortcuts experience - Capability to design, build, and ship personalized recommendations serving millions of listeners globally - Skill in building content recommendation systems for emerging agentic and AI-powered user experiences - Ability to 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 supporting personalization at scale - Contribute to the long-term architecture of personalization systems - Care deeply about creating high-quality user experiences through thoughtful application of machine learning - Influence technical decisions beyond immediate team Compensation: - United States base range: $227,495 – $324,993 plus equity - Benefits include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don’t miss this opportunity to join a forward-thinking team!