The role is for a senior engineer in the Consumer ML Serving team at Netflix, focusing on developing and owning the long-term vision for machine learning and artificial intelligence applications. This team provides the computational platform for consumer-facing ML/AI applications, including real-time model serving and infrastructure for large language models. The position requires collaboration with engineers, product managers, and data scientists to enhance Netflix's ML initiatives. Candidates should be passionate about building robust systems and enjoy seeing the impact of their work on customer experiences.

• Experience building and operating high-traffic, real-time distributed systems.
• Familiarity with ML serving infrastructure for large foundation models.
• Ability to translate research requirements into generic platform offerings.
• Experience delivering high availability, throughput, and performance systems.
• Proficiency in object-oriented programming languages, preferably Java.
• Experience with public cloud services such as AWS, Azure, or GCP.
• A BS/MS in Computer Science, Applied Math, Engineering, or a related field.

• Own and develop the long-term vision for ML/AI initiatives.
• Collaborate with cross-functional teams to enhance ML applications.
• Build and maintain scalable and robust ML infrastructure.
• Lead projects and guide other engineers in the team.
• Execute zero-to-one projects in highly ambiguous environments.
• Ensure the delivery of high-quality, well-tested code.

• 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.