Senior Machine Learning Engineer, Surfaces Moments

Spotify

Senior Machine Learning Engineer in Personalization team at Spotify. Driving recommendations and user engagement through machine learning and AI systems.

Posted 7/23/2026full-timeRemote • New York • 🇺🇸 United StatesSenior💰 $184,050 - $262,928 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and deploying machine learning systems, particularly in recommendation systems and large language model optimization. Proficient in Python and experienced with data pipeline orchestration and A/B testing to enhance user experiences.

Highest-signal resume keywords

Machine Learning Systems DevelopmentRecommendation Systems ExpertisePython ProficiencyLarge Language Model TrainingData Pipeline Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningRecommendation SystemsLarge Language ModelsSupervised Fine-TuningDistillationParameter-Efficient TrainingA/B TestingModel EvaluationCost OptimizationContent Discovery

Soft Skills

Effective CommunicationCollaboration

Tools & Technologies

PyTorchFlyteAirflowBigQueryCloud-Based Storage

Industry Keywords

PersonalizationUser ExperienceProduction EnvironmentsLatency ChallengesReliability

Tech Stack

Tools & technologies

AirflowBigQueryCloudPythonPyTorch

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

5+ 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
experienced with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA
worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization
care deeply about creating high-quality user experiences through thoughtful application of machine learning
communicate effectively across technical and non-technical audiences and enjoy working in highly collaborative environments
know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes
experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms

Benefits

Comp & perks

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