The Machine Learning Scientist role at Netflix focuses on developing innovative ML solutions to enhance content promotion and discovery. The position is part of the Promotional Assets & Creative Technology AIMS team, which aims to push the boundaries of storytelling through advanced technology. The scientist will track advancements in LLM and generative models, applying state-of-the-art techniques to high-impact problems. This role involves collaboration with ML scientists and engineers to integrate models into business applications.

• Demonstrated habit of tracking LLM and generative model literature.
• Strong foundation in ML and Deep Learning, especially in Natural Language Processing.
• Research experience in summarization or generated-text evaluation is a plus.
• Expertise in one or more LLM post-training approaches.
• Experience with recommendation systems or personalization is a strong plus.

• Track advancements in LLM and generative model research and translate them into opportunities.
• Apply state-of-the-art techniques to problems such as summarization quality.
• Lead end-to-end ML development on high-impact problems.
• Optimize generated content for member impact by treating content generation and audience targeting as coupled problems.
• Partner with ML scientists and engineers to integrate models into business applications.
• Translate complex technical concepts for both technical and non-technical stakeholders.
• Act as a subject matter expert to identify high-impact opportunities and define roadmaps.
• Engage with the ML community to learn, teach, and contribute to building the Netflix brand.

• 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.