🛠 Tech Stack

💼 About This Role

You'll work on podcast recommendation systems that power experiences like Home and Now Playing. You'll collaborate with teams across Personalization and Podcast Mission to evolve podcast listening. Your work will directly shape transformer-based models for millions of listeners.

🎯 What You'll Do

• Design and scale reward signals for recommendations via hands-on ML development
• Promote best practices of ML systems development and evaluation
• Lead collaborations to integrate and A/B test mid-term signals across recommendation systems

📋 Requirements

• Strong background in machine learning with expertise in statistics and optimization
• Hands-on experience with production ML systems at scale in Java, Scala, or Python
• Experience with PyTorch, Ray, Hugging Face or similar tools
• Experience with large-scale distributed data processing like Apache Beam or Spark

✨ Nice to Have

• Experience with sequential models, transformers, generative AI, and LLMs
• Experience with cloud platforms like GCP or AWS
• Knowledge of agile software processes and data-driven development

🎁 Benefits & Perks

• 🏖️ Flexible work - work remotely within North America
• 🏢 Collaborative culture - work with cross-functional teams
• 📈 Impact - shape recommendations for millions of users

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Onsite/Panel· 2 hours