AI Research Engineer 6 - TL, Algo Core - AI for Member Systems

• Drive the team’s technical vision and roadmap for reward modeling, utility estimation, and multi-objective optimization — including auction-based and constrained-optimization approaches to allocating promotional real estate.
• Drive cross-functional partnerships with Merchandising, Ads, MECS, Product, and Data Science & Engineering to align AI/ML capabilities with business priorities.
• Partner with the Personalization Foundations team to integrate and leverage the utility layer, reward signals, and multi-objective optimization across all member-facing AI models.
• Design and run rigorous offline experiments and A/B tests to validate the impact of new reward, utility, and multi-objective optimization systems on key business and member-experience metrics.
• Contribute to the team’s technical culture through mentorship, code review, and raising the bar on engineering practices.

What we are looking for:

• 6+ 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.
• Master’s or PhD in a computational field such as computer science, statistics, math, operations research, or physics.
• Deep expertise in ML and optimization algorithms and frameworks, with hands-on experience training, tuning, and deploying models in production.
• Experience with reward modeling, utility estimation, or constrained-optimization and auction-based allocation systems.
• Strong software engineering skills in Python, plus experience with Scala or Java.
• Strong 80/20 mindset: ability to scope the right problem, ship pragmatically, and maintain rigorous standards without over-engineering.

NOTE: This role sits within Algo Core, the horizontal team inside AI for Member Systems (AIMS) that owns reward modeling, utility estimation, and multi-objective optimization.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

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.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $600,000.00 - $1,066,000.00. This compensation range will vary based on location.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Algo Core is a horizontal team within AI for Member Systems (AIMS) that owns reward modeling, utility estimation, and multi-objective optimization as shared capabilities used across Netflix’s recommendation, personalization, and promotion systems. We’re looking for a Research Engineer to serve as technical lead for this surface area — driving the roadmap for how Netflix combines member value and business value into a single, tunable framework (using auction-based and constrained-optimization techniques) for deciding what gets promoted where across the member experience.