Spotify

Spotify

Staff Machine Learning Engineer, Home Surfaces

New York, NY · Staff+

Sponsorship not specified$227k-$325kDetected 30 days ago
PythonBigQueryMachine LearningAirflowData EngineeringNLPLLMsA/B TestingResearch

Stay score

odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level IV · 4×
Level I$109,8451 entry
Level II$137,7172 entries
Level III$165,5893 entries
Level IV$193,4614 entries

This range already reaches Level IV — the maximum four lottery entries.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · New York-Newark-Jersey City, NY-NJ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • The Personalization team makes deciding what to play next easier and more enjoyable for every listener.
  • From Blend to Discover Weekly, we're behind some of Spotify's most-loved features.
  • We built them by understanding the world of music and podcasts better than anyone else.

Responsibilities

  • 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.
  • The Surfaces Podcasts team owns podcast recommendations across some of Spotify's most visible surfaces, including Home and the Now Playing view.
  • We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences.
  • You communicate effectively with technical and non-technical partners and can influence technical decisions beyond your immediate team.

Requirements

  • You have deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
  • 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 are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones.

Compensation

  • $227k-$325k

Benefits

  • Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.
  • Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team.
  • You have deep experience building and deploying machine learning systems in production environments.
  • You are proficient in Python and have hands-on experience building machine learning systems with PyTorch.
  • As a Staff Machine Learning Engineer, you'll help shape the future of personalized discovery and engagement at Spotify.
  • You'll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences for listeners at global scale.
  • You care about creating high-quality user experiences through thoughtful applications of machine learning.
  • You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.

Company info

  • Where You'll Be - We offer you the flexibility to work where you work best!
  • At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone.
  • Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators.
Apply directly at Spotify →Create a free account for alerts like thisView Spotify immigration profile

This listing is sourced directly from Spotify's careers page and normalized into a canonical job model.