Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

The ML UI Tooling team builds UI tools to enhance the productivity and efficiency of all ML practitioners across Netflix. The team owns and operates a centralized ML lifecycle visualization platform that provides a comprehensive and centralized way for ML practitioners across Netflix to manage ML models, featuring visualization, observability, and performance benchmarking capabilities.

We seek skilled engineers to develop and expand our model observability and visualization workflows to support bandits, multi-task learning models, Large Language Models (LLMs), and other foundation models. Our tools and systems support and enable 100s of ML practitioners to develop some of Netflix’s most business-critical models across personalization, growth and commerce, ads, and studio algorithms. You will be highly cross-functional, partnering with other engineers, product managers, machine learning engineers, and data/research scientists to elevate our ML/AI initiatives and drive impactful innovation.

Snapshot of projects you may work on:

• Observability dashboard and corresponding backend system to integrate with various MLP products to enable ML practitioners to explore and discover ML entities (models, features, embeddings, pipelines, etc.) and monitor and operate them effectively.
• Collaborate with cross-functional teams to implement anomaly and drift detection visualization on models, features, embeddings, etc.
• Cost monitoring and chargeback dashboards to provide visibility into resource utilization and identify opportunities for efficiency improvements.
• Enhance our user interfaces to provide intuitive and seamless experiences for ML practitioners, incorporating feedback and best practices to improve usability and adoption.

We would love to work with you if:

• You have experience building backend distributed systems and full-stack systems using object-oriented programming (preferably Java, Scala) and web API frameworks (preferably Spring Boot).
• You have experience working with the public cloud, like AWS, Azure, or GCP.
• You have the ability to learn and use in-house software framework/components/services to build solutions effectively.
• You have experience maintaining and improving legacy systems and can evaluate and discuss tradeoffs regarding refactoring, rebuilding, and buying.
• You proactively communicate with cross-functional teams to drive projects and promote best practices in observability and logging.
• You have a BS/MS in Computer Science, Applied Math, Engineering, or a related field.
• You have experience working with teams distributed across multiple time zones.

We would prefer to work with you if:

• You have knowledge of ML model lifecycle management to build end-to-end visualizations spanning development, deployment, and monitoring of ML models.

To learn more about our ML Platform, you can review the relevant talks/blog posts on the Netflix ML Platform Research website.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.