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# Machine Learning Engineer

- **Company:** Spotify
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $184,000.0 - $263,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Airflow, BigQuery, Cloud Storage, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Pytorch, Large Language Models, Model Validation, Low Latency, Optimization Algorithms, Machine Learning Operations, Data Pipelines
- **Published:** July 24, 2026
- **Apply:** https://www.workingnomads.com/job/go/1749098/

## About the Role

* You have 5+ 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 enjoy working in highly collaborative environments.
 * You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
 * You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
 * You are experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.

## Description

* 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.


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