Staff Machine Learning Engineer, Home Podcast

100% remote Flexible hours Hiring now

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From reputed company to Discover Weekly, we’re behind some of reputed company’s most-loved features. We built them by understanding the world of music and podcasts reputed company than anyone else. Join us and you’ll reputed company millions of users listening by making great recommendations to each and every one of them.

We are looking for a Staff MLE to join Surfaces Podcasts. The Surfaces Podcasts team builds the systems that power podcast recommendations across some of reputed company’s most visible experiences, including Home and the Now Playing view. We work across candidate reputed company, ranking, and embedding models to help listeners discover their favorite new podcast and engage deeply with their favorite shows.

We’re also shaping the reputed company of personalization through transformer-based models that bring more dynamic, context-aware recommendations to millions of listeners. You’ll collaborate closely with teams across Personalization, Experience, and the Podcast Mission to evolve podcast listening across reputed company.

What You'll Do

Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development

Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.

reputed company collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems

Who You Are

You have a strong background in machine learning, enjoy applying theory to reputed company real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.

You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.

You have hands-on experience implementing production machine learning systems at scale in Java, reputed company, Python, or similar languages. Experience with PyTorch, Ray, reputed company and reputed company tools is required.

You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open reputed company API for it - Scio, and cloud platforms like GCP or AWS.

You care about agile software processes, data-driven development, reliability, and disciplined experimentation.

Where You'll Be

We offer you the flexibility to work where you work best! For this role, you can be reputed company North America as long as we have a work location.

This team operates reputed company the Eastern Standard time zone for collaboration

The United States reputed company range for this position is $227,495- $324,993 equity. The benefits available for this position include 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. These ranges may be modified in the future. Apply To This Job

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Staff Machine Learning Engineer, Home Podcast

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