Research Scientist L5, Algorithms Engineering
Netflix
On-site 🏢 23 July
R&D, Innovation
California, United States 🇺🇸
Netflix is one of the world’s leading entertainment services with 278 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The Role
NOTE: This job posting is inclusive of a variety of positions within our Algorithms 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. Netflix is one of the world's leading entertainment services with 270 million paid memberships in over 190 countries enjoying series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time. As Netflix continues to grow, we are venturing into exciting new frontiers of personalization to help our members find the content they’ll most enjoy. We are looking for exceptional individuals to work full-time with us as research scientists. In this role, you will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes researching and applying cutting edge machine learning algorithms, running offline experiments, and building online A/B tests to run in production systems. To be successful in this role, you need a strong machine learning background, solid software development skills, a love of learning, a passion for solving end-user problems and to collaborate well in multi-disciplinary teams. You will need to exhibit strong communication and leadership skills, an ability to handle ambiguity and set priorities, and an execution focus in a dynamic environment. What we are looking for:- A burning desire to solve real-world problems at scale by applying Machine Learning.
- PhD or Masters in Computer Science, Statistics, or a related field.
- 5+ years of applied research experience with a track record of delivering quality results.
- Experience in applied research in industrial settings.
- Expertise in machine learning spanning supervised, self-supervised, and bandit learning methods.
- Strong mathematical and problem-solving skills with knowledge of statistical methods.
- Excellent software engineering skills in Python along with Scala or Java or C++ or C#.
- Experience in one or more of the following applied fields: Recommendations, Personalization, long-term reward modeling, Bandits, Transformers.
- Great interpersonal skills including strong written and verbal communication.
- Experience as a technical leader.
- Experience working with cross-functional teams.
- Experience in one or more of Search, Natural Language Processing, Knowledge Graphs, Conversational Agents, Personalization, and Causal Inference, Reinforcement Learning, etc.
- Experience with cloud computing platforms and large web-scale distributed systems.
- Open source contributions.
- Research publications at peer reviewed journals and conferences on relevant topics.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
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Milano, Italy 🇮🇹
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On-site 🏢 10 August
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Washington, United States 🇺🇸
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Research Assistant - PFE 2025
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R&D, Innovation
Casablanca, Morocco 🇲🇦
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On-site 🏢 17 September
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On-site 🏢 02 October
R&D, Innovation
Seattle, United States 🇺🇸
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On-site 🏢 29 July
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On-site 🏢 22 September
R&D, Innovation
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Research Assistant - PFE 2025
On-site 🏢 10 August
R&D, Innovation
Casablanca, Morocco 🇲🇦
ASIC Physical Design Intern
On-site 🏢 15 October
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Shanghai, China 🇨🇳
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Remote 🌎🌍🌏 21 October
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Hybrid 🏡🏢 28 October
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Remote 🌎🌍🌏 22 October
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