Research Engineer – AI for Member Systems

Research Engineer – AI for Member Systems at Netflix

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 – AI for Member Systems to join our AI for Member Systems group. 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 machine learning and software engineering.

What We Are Looking For

• 5+ years of experience in applying machine learning in an industrial setting, with a track record of delivering impactful results.
• PhD or Masters in Computer Science, Statistics, or a related field.
• Expertise in machine learning algorithms and frameworks, with hands-on experience in training, tuning, and deploying models in production environments.
• Excellent software design and development skills in Python along with Scala, Java, C++, or C#.
• Experience in one or more of the following applied fields: Recommendations, Personalization, Long-term Reward Modeling, Bandits, Transformers, Large-Scale Language Models, LLM evaluation, RLHF reward modeling/alignment.
• Great interpersonal skills including strong written and verbal communication.

Preferred Qualifications

• Experience building or enhancing personalization systems, search engines, or similar large-scale machine learning applications.
• Background in neural networks, natural language processing, or causal inference.
• Contributions to open-source projects in machine learning or related fields.
• Experience working with cross functional teams.

Key skills/competency

• Machine Learning
• Software Engineering
• Personalization Systems
• Recommendation Algorithms
• A/B Testing
• ML Infrastructure
• Python
• Scala/Java/C++/C#
• Large-Scale Systems
• AI/NLP/Causal Inference