Senior Machine Learning Manager, Merchandising and Content Understanding
NetflixUSA - Remote$676k – $1195kPosted 23 April 2026
Tech Stack
Job 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.
The Merchandising and Content Understanding Data Science and Engineering organization shapes how members discover and engage with Netflix. We build foundational algorithmic capabilities and agentic frameworks for content understanding that power merchandising, discovery, ratings, and a wide range of applications across Netflix.
We are seeking a Senior Manager to lead a group of Research Scientists, ML Engineers, Data Scientists, and Analytics Engineers focused on Multimodal Large Language Models (MLLMs) and agentic systems for deep, complex content understanding. In this role, you will own a multi‑domain portfolio, define strategy, and drive high‑impact algorithmic systems that shape how Netflix represents and merchandises its catalog globally.
Responsibilities
Define and execute a cohesive strategy for how MLLMs and agentic systems power deep, complex content understanding applications across Netflix.
Oversee end‑to‑end initiatives spanning research, ML engineering, measurement science, and continuous improvement.
Manage and grow a multidisciplinary organization: attract and retain top talent across levels and disciplines; develop strong technical leaders and managers.
Shape the organizational structure, operating model, and interfaces between teams to maximize leverage, alignment, and velocity.
Partner closely with cross‑functional leaders to define long‑term roadmaps for content understanding.
Bring deep, hands‑on expertise in MLLMs and agentic systems to guide technical direction and strategic bets.
Establish best practices and elevate technical excellence for complex algorithmic and agentic systems operating at Netflix scale.
Act as a key thought leader in the broader Netflix ML community - sharing learnings, mentoring leaders, and raising the bar across the company.
About you
Proven track record leading multidisciplinary, highly technical algorithmic teams with responsibility across multiple domains or sub‑teams.
Experience operating at a senior‑manager (or equivalent) level, including setting org‑level strategy, managing managers and technical leads, and influencing cross‑organizational priorities.
Demonstrated experience taking advanced MLLM and agentic systems from research to production and continuously improving those systems post‑launch at scale.
Skilled at bringing structure to highly ambiguous, fast‑evolving problem spaces; able to connect long‑term bets in foundational models and agentic systems with near‑term product use cases and business value.
Strong record of recruiting, mentoring, and developing senior ICs, tech leads, and managers; known for building inclusive, high‑trust, high‑performance cultures where people do the best work of their careers.
Exceptional verbal and written communication skills; adept at sharing compelling visions and shaping decisions that affect multiple organizations.
Master’s or PhD in Machine Learning, Computer Science, or a closely related field (or equivalent practical experience).
6+ years of hands‑on ML experience (or 4+ years with a relevant PhD), including substantial work in modern deep learning.
3+ years leading ML teams, with at least 1–2 years managing multiple teams or leaders (e.g., senior manager, group lead, or equivalent).
Deeply committed to delivering end‑to‑end business impact.
Netflix culture resonates with you.
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 re ... (truncated, view full listing at source)
Apply Now
Direct link to company career page
AI Resume Fit Check
See exactly which skills you match and which are missing before you apply. Free, instant, no spam.
Check my resume fitFree · No credit card