Research Engineer 5/6 – AI for Member Systems

Benefits

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Not verified last checked Jun 13, 2026

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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About this role

Research Engineer 5/6 – AI for Member Systems USA - Remote 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. As Netflix continues to grow, so do the opportunities to enhance our personalization systems and algorithms. We're looking for a passionate and talented Research Engineer to join our Al for Member Systems. In this role, you will apply your expertise in machine learning and software engineering to design, develop, and scale solutions that power the Netflix experience. Key Responsibilities: Collaborate with cross-functional teams, including researchers, engineers, data scientists, and product managers, to develop and implement machine learning algorithms that improve personalization, recommendations, and member experiences. Create scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment in Netflix's large-scale, real-time systems. Optimize the performance and scalability of machine learning models, ensuring they can handle the diverse tastes and behaviors of our global member base. Design and conduct offline experiments and A/B tests to validate the impact of algorithmic changes on key business metrics. Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices. Engage in continuous learning and development, staying up-to-date with the latest advances in

Read the full description at explore.jobs.netflix.net. FewerJobs shows a source-linked preview and links to the original posting.