Responsibilities
- Build and productionize recommendation models using collaborative filtering, content-based, hybrid, and deep learning approaches.
- Design ranking and retrieval pipelines for low-latency, high-scale serving.
- Partner with product, data science, and engineering teams to define personalization strategy.
- Run offline and online experiments and iterate using CTR, retention, and revenue-lift metrics.
- Improve data pipelines, feature stores, and model monitoring for reliability and model quality.
- Contribute to MLOps practices including model versioning and observability.
Requirements
- 5+ years of experience in machine learning engineering, recommendation systems, or ranking.
- Strong Python skills and experience with ML frameworks such as PyTorch or TensorFlow.
- Experience with large-scale data tools such as Spark, Kafka, Airflow, and SQL.
- Hands-on experience deploying machine learning models to production.
- Solid understanding of relevance and ranking metrics and experimentation methodology.
- Strong communication and cross-functional collaboration skills.
- Preferred: PhD in Computer Science.
- Preferred: experience with mobile development.
- Preferred: experience with real-time personalization and feature stores.
Tech Stack
Categories
About ByteDance
ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. We are committed to building a safe, healthy and positive online environment for all our users. We have over 110,000 employees based in more than 30 countries globally. Join us.