Staff Machine Learning Engineer
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Science · Software Engineering
In short
Spotify is hiring a Staff Machine Learning Engineer to work on personalization and recommendation systems for the Home Surfaces team. This role involves developing and deploying ML models, including large language models, to enhance user experiences and drive engagement. The position requires strong expertise in Python, PyTorch, and production-scale ML infrastructure.
Responsibilities
- Own and improve machine learning models and systems powering the Home feed and Shortcuts experience.
- Design, build, and ship personalized recommendations for 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 like SFT, distillation, and parameter-efficient training.
- Partner 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 for personalization at scale.
- Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of personalization systems.
- Mentor and support other machine learning engineers.
Requirements
- 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.
- Strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.
- Experience with large language model training, fine-tuning, evaluation, and optimization techniques (SFT, distillation, LoRA).
- Experience with large-scale inference systems and understanding of latency, reliability, and cost optimization challenges.
- Effective communication across technical and non-technical audiences, influencing technical decisions beyond the immediate team.
- Experience designing, executing, and interpreting online experiments and A/B tests.
- 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.
Desired Qualifications
- You care deeply about creating high-quality user experiences through thoughtful application of machine learning.
Benefits
- United States base range: $227,495 - $324,993 plus equity.
- Health insurance.
- Six months paid parental leave.
- 401(k) retirement plan.
- Monthly meal allowance.
- 23 paid days off.
- 13 paid flexible holidays.
- Paid sick leave.
- Extensive learning opportunities through GreenHouse.
- Flexible share incentives.
- All The Feels, employee assistance program and self-care hub.
- Flexible public holidays, swap days off according to your values and beliefs.
#Machine Learning#Recommendation Systems#LLM#Personalization#Python#PyTorch#A/B Testing#Data Pipelines
Company
Spotify
Job Posted
1 week ago
Employment Type
Full Time
WorkMode
Remote
Experience Level
Senior
Locations
New York, United States
Applicants
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