Staff Machine Learning Engineer – Home Surfaces

Spotify

Staff Machine Learning Engineer building Spotify’s personalized Home and recommendation systems. Developing LLM-powered discovery experiences and production-scale ML infrastructure for millions of listeners.

Posted 9/10/2026full-timeRemote • New York • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in building and deploying machine learning systems, particularly in recommendation systems and large language models. Proficient in Python and capable of optimizing data pipelines and orchestration workflows for scalable personalization solutions.

Highest-signal resume keywords

Machine Learning Systems DevelopmentRecommendation Systems ExpertisePython ProficiencyLarge Language Model OptimizationA/B Testing and Experimentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningRecommendation SystemsLarge Language ModelsPythonPyTorchA/B TestingData Pipeline DevelopmentDistributed Machine LearningModel EvaluationCost Optimization

Soft Skills

Effective CommunicationInfluencing Technical DecisionsMentoring

Tools & Technologies

RayFSDPHSDPFlyteAirflowBigQueryCloud-Based Storage

Industry Keywords

PersonalizationContent DiscoveryMachine Learning PlatformsModel TrainingContinuous Optimization

Tech Stack

Tools & technologies

AirflowBigQueryCloudPythonPyTorchRay

About the role

Key responsibilities & impact

Own and improve the machine learning models and systems powering Spotify's Home feed, including the 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 SFT, distillation, and parameter-efficient training approaches
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 supporting personalization at Spotify 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

What you’ll need

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
Hands-on experience building machine learning systems with PyTorch
Experience with large language model training, fine-tuning, evaluation, and optimization, including SFT, distillation, and LoRA
Experience with large-scale inference systems and latency, reliability, and cost optimization
Ability to design, execute, and interpret online experiments and A/B tests
Experience operating distributed machine learning workloads using Ray, FSDP, HSDP, or similar frameworks
Experience building and maintaining data pipelines and orchestration workflows using Flyte, Airflow, BigQuery, and cloud-based storage platforms
Effective communication across technical and non-technical audiences
Ability to influence technical decisions beyond the immediate team

Benefits

Comp & perks

Equal opportunity employer
Reasonable accommodation support throughout the recruitment and interview process
Flexible remote work within the North Americas region where Spotify has a work location