{"id":3887300,"url":"https://alion.io/job/netflix-research-engineer-6-tl-messaging-algorithms","title":"Research Engineer 6 - TL, Messaging Algorithms","company":{"id":5888,"name":"Netflix","domain":"netflix.com","url":"https://alion.io/company/netflix","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":86,"open_postings":75,"ghost_share":0,"stale_share":0.373,"repost_share":0,"time_to_fill_p50_days":72,"computed_at":"2026-11-08T05:47:12Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Gatos, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":600000,"max":null,"currency":"USD","period":"year","gross":null,"usd_annual":600000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false}],"status":"closed","first_seen_at":"2026-11-04T00:00:00Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-08T22:40:41Z","board_verified":false,"closed_at":"2026-11-08T22:40:41Z","days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"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.\nThe 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).\nThe team is organized into three areas:\nCandidate Generation: Scaling the message catalog via creator tooling integrations and GenAI message creation \nSend Decision Optimization: Improving targeting decisions across the notification system\nEmerging Applications: Expanding message personalization into new business areas and member states including Podcasts, FTAB, and Commerce applications. \nAbout the Role\nThis 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.\nWhat makes this role unique:\nCross-functional leadership. You'll drive partnerships with Merchandising, Product Management, Data Science & Engineering to develop scalable, well-integrated designs.\nHigh-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.\nGenAI 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.\n 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.\nResponsibilities\nDrive the team’s technical vision and roadmap for candidate generation and emerging applications\nDrive cross-functional partnerships with Merchandising, Product, Engineering, and Data Science & Engineering to align ML capabilities with business priorities\nDesign, build, and ship production ML systems that scale across Netflix's ecosystem\nPartner with the AIMS AI Foundations team to integrate and leverage foundation model capabilities for member-facing use cases\nDesign and run rigorous offline experiments and A/B tests to validate the impact of new systems on key business metrics\nContribute to the team's technical culture through mentorship, code review, and raising the bar on engineering practices\nWhat We're Looking For\n10+ years of experience applying machine learning in an industry setting, with a track record of delivering impactful production systems\nExperience driving successful partnerships with both technical and nontechnical stakeholders\nMasters or PhD in a computational field such as physics, computer science, statistics, or math \nDeep expertise in ML algorithms and frameworks, with hands-on experience training, tuning, and deploying models in production\nExperience with personalization, recommendations, or search algorithms \nStrong software engineering skills in Python, plus experience with Scala or Java\nStrong system design skills, keeping operational simplicity in mind \nStrong 80/20 mindset: ability to scope the right problem, ship pragmatically, and maintain rigorous standards without over-engineering\n\nGenerally, 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.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.\nNetflix is a unique culture and environment. Learn more here.\nInclusion 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.\nWe are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. 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