Staff Machine Learning Engineer, Home Surfaces

pofft Technology Inc.; Canada; Remote; CAD 254,000 - 339,000; Full time

Job summary

Spotify is seeking a Staff Machine Learning Engineer for the Home Surfaces area to advance personalized discovery and engagement at scale. You will shape models powering the Home feed and Shortcuts, collaborating with product, data science, and engineering teams to deliver high-quality recommendations to millions of listeners worldwide.

You will drive training and optimization of ML models, including LLMs, and scale ML infrastructure for low-latency, cost-efficient personalization while

Qualifications

• 8+ years of experience building and deploying ML systems in production.
• Deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
• Strong proficiency in Python and hands-on experience with PyTorch.
• Experience with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA.
• Experience with large-scale inference systems and latency/cost challenges.

Responsibilities

• Own and improve ML models and systems powering the Home feed and Shortcuts experiences.
• Design, build, and ship personalized recommendations for millions of listeners globally.
• Build content recommendation systems for agentic and AI-powered user experiences.
• Train, fine-tune, evaluate, and optimize LLMs using SFT, distillation, and LoRA techniques.
• Collaborate with product managers, engineers, data scientists, and designers to run experiments and strategies.

Skills

Python

PyTorch

Recommendation systems

LLM training

SFT

Distillation

LoRA

Online experimentation

Production ML systems

Communication

Job description

Staff Machine Learning Engineer, Home Surfaces

Staff Machine Learning Engineer, Home Surfaces Remote 1 gün 17 saat 52 dakika önce yayınlandı. Jobicy -

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. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.

As a Staff Machine Learning Engineer, you will 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 that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, driving technical direction in ambiguous problem spaces, and solving complex personalization challenges at global scale.

What You’ll Do

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.

Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of personalization systems.

Mentor and support other machine learning engineers, helping raise the bar across the team.

Who You Are

You have 8+ years of experience building and deploying machine learning systems in production environments.

You have deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.

You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.

You are experienced 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 care deeply about creating high-quality user experiences through thoughtful application of machine learning.

You communicate effectively across technical and non-technical audiences, and you influence technical decisions beyond your immediate team

You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.

Payment Type

-

Price Range

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Work Type

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Location

Remote