JobsProduct Machine Learning Research Leader
Job description
The role is for an experienced leader in the Machine Learning & Inference Research (MLIR) team at Netflix, focusing on developing and executing strategies that integrate cutting-edge methods into the company's operations. The leader will manage a portfolio of foundational research and collaborative projects that enhance member experience and business insights. This position requires a strong understanding of business needs and the ability to translate them into a long-term research agenda. The leader will also foster collaboration and innovation within the team and across the organization.
Requirements
- Ph.D. in a quantitative field such as Mathematics, Computer Science, Statistics, Physics, Operations Research, or Economics.
- Proven experience in building and leading a research program.
- Outstanding oral and written communication skills.
- Experience operating in a collaborative environment across multiple disciplines.
- Demonstrated success in fostering an inclusive team culture.
Responsibilities
- Inspire and lead a senior team of research scientists in machine learning and causal inference.
- Collaborate with various partners to maintain a strong portfolio of impactful projects.
- Uplevel research best practices and organizational expertise in machine learning.
- Help prioritize and balance competing priorities for the long-term benefit of Netflix.
- Build a successful research program that includes research scientists and external collaborations.
Benefits
- Employees at Netflix are often offered flexible, people-first benefits—unlimited time away, generous parental leave, global family-forming support, mental-health programs (mindfulness, free counseling/coaching), and health coverage tailored by country. Financially, Netflix pays at personal top-of-market and lets employees choose their mix of cash vs. fully-vested 10-year stock options, alongside donation and volunteer matching. Convenience perks can include trust-based travel/expense policies, relocation support, and “Work, Not Drive” rideshare flexibility.
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