🛠 Tech Stack

💼 About This Role

You'll lead recommendation and personalization research for a global anime streaming platform. You'll design and deploy ranking and retrieval systems that shape how 100 million fans discover content. This role combines scientific rigor with product impact across video, manga, and ecommerce surfaces.

🎯 What You'll Do

• Lead research on recommendation, ranking, and personalization algorithms.
• Design offline evaluation frameworks for recommender systems.
• Partner with product and engineering to run online experiments.
• Develop user and content representations via feature engineering and deep learning.
• Translate research prototypes into production solutions with ML engineers.

📋 Requirements

• 5+ years of experience in applied ML or recommendation systems.
• MS or PhD in CS, ML, Statistics, or related quantitative field.
• Proficiency in Python and ML libraries like PyTorch, TensorFlow, or scikit-learn.
• Experience with recommender systems such as collaborative filtering or sequence modeling.

✨ Nice to Have

• Experience personalizing media, entertainment, or subscription products.
• Familiarity with recommender system failure modes like popularity bias or cold start.
• Experience with multi-objective optimization or constrained ranking.

🎁 Benefits & Perks

• 🏖️ Unlimited PTO
• 💰 401(k) matching
• 🏥 Comprehensive health insurance
• 📚 Learning and development stipend
• 🎟️ Free Crunchyroll subscription

📨 Hiring Process

Estimated timeline: 3-5 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Phone Interview· 60 min
3. 3Onsite Interviews (4 rounds)· 4 hours