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

Links:

• Netflix Research site

• Our long term business view

NOTE: This job posting is inclusive of a variety of positions within our AI for Member Systems (AIMS) Engineering group. Based on your background, expertise and interests, we will route you to the appropriate team(s). All teams may not be hiring at the same time.