Research Engineer 6 - TL, Messaging Algorithms

About the role

The Notifications Personalization team owns the algorithmic targeting, ranking, and pacing of notifications to Netflix members. We build the ML systems that decide which messages to send, to whom, when, how often, and via which channel. The team partners closely with the broader ML organization (ML Platform, Recommendations, Foundation Models) and the broader messaging ecosystem (Messaging Engineering, Product, CRM, Live, Games).

The team is organized into three areas

Candidate Generation: Scaling the message catalog via creator tooling integrations and GenAI message creation

Send Decision Optimization: Improving targeting decisions across the notification system

Emerging Applications: Expanding message personalization into new business areas and member states including Podcasts, FTAB, and Commerce applications.

About the Role

This position is a tech lead role within the team. You will co-own vision and strategy, as well as drive execution for key technical initiatives across teams. You will own production ML systems at the intersection of product and platform, spanning GenAI-powered message and asset creation, Commerce, and new content experiences.

• What makes this role unique: Cross-functional leadership.
• You'll drive partnerships with Merchandising, Product Management, Data Science & Engineering to develop scalable, well-integrated designs.
• High-leverage, high-visibility scope
• . Messaging touches every Netflix member. The systems you build will directly drive engagement, retention, and revenue across some of Netflix's fastest-growing business areas.
• GenAI meets product.
• Personalized message is a natural application of multimodal AI. You'll be at the forefront of bringing GenAI capabilities into a production messaging system at global scale.
• 0 → 1 and optimization.
• The role spans building entirely new systems from scratch (Rejoin message personalization, GenAI message creation) and applying advanced methods to further optimize existing levers.

Responsibilities

• Drive the team’s technical vision and roadmap for candidate generation and emerging applications
• Drive cross-functional partnerships with Merchandising, Product, Engineering, and Data Science & Engineering to align ML capabilities with business priorities
• Design, build, and ship production ML systems that scale across Netflix's ecosystem
• Partner with the AIMS AI Foundations team to integrate and leverage foundation model capabilities for member-facing use cases
• Design and run rigorous offline experiments and A/B tests to validate the impact of new systems on key business metrics
• Contribute to the team's technical culture through mentorship, code review, and raising the bar on engineering practices

What We're Looking For

• 10+ years of experience applying machine learning in an industry setting, with a track record of delivering impactful production systems
• Experience driving successful partnerships with both technical and nontechnical stakeholders
• Masters or PhD in a computational field such as physics, computer science, statistics, or math
• Deep expertise in ML algorithms and frameworks, with hands-on experience training, tuning, and deploying models in production
• Experience with personalization, recommendations, or search algorithms
• Strong software engineering skills in Python, plus experience with Scala or Java
• Strong system design skills, keeping operational simplicity in mind
• Strong 80/20 mindset: ability to scope the right problem, ship pragmatically, and maintain rigorous standards without over-engineering