The Content Discovery and Personalization team at Netflix is seeking an experienced Research Engineer to enhance the understanding of members through research and development of LLM prototypes. This role focuses on improving decision-making capabilities by building scalable data products and providing frameworks for better member interaction. The ideal candidate will leverage their expertise in machine learning and LLMs to drive insights and influence product direction. Collaboration with data scientists and engineers is essential to maximize understanding of members.

• You have a strong foundation in deep learning and LLMs with proven hands-on industry experience.
• You have substantial relevant industry experience building scalable ML models, particularly in natural language processing.
• You hold an advanced degree (PhD) in Computer Science, Electrical Engineering, or a related technical field.
• You have strong software engineering skills in Python and are proficient in frameworks such as PyTorch or TensorFlow.
• You excel at solving complex problems with innovative solutions and adapting existing methods from literature.

• Research, develop, and iterate on LLM/ML evaluation and simulation systems.
• Drive your own roadmap, determining areas for rapid iteration and deeper development.
• Create insights and help shape the direction of future member-facing investments.
• Collaborate with Data Scientists, ML Scientists, and Engineers on various projects.
• Stay up to date with research in areas related to LLM advancement and implement new best practices.

• 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.