# Senior Machine Learning Engineer, Surfaces Moments

**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** Machine Learning, Recommendation Systems, LLMs, PyTorch, Python, sft, distillation, lora, A/B Testing, Ray, flyte, Airflow, BigQuery
**Posted:** 2026-06-18

> Senior ML Engineer on the Surfaces Moments team building personalized Home feed experiences and recommendation systems for Spotify listeners. Own models from research to production, fine-tune LLMs, drive A/B experiments, and optimize large-scale inference and data pipelines.

## Job Description

## 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.

## Who You Are
- 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.
- Experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
- Experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.

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