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Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training)
full-timeNew York, Los Gatos

Summary

Location

New York, Los Gatos

Type

full-time

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About this role

Netflix is one of the world's leading entertainment services, with over 300 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.

As Netflix grows, we keep advancing innovations in personalization and discovery, experimentation and decision-making, understanding our members and our titles, and backend infrastructure. These developments constantly create new opportunities for research to drive meaningful impact. By exploring the frontiers of AI/ML and intersecting fields, the Machine Learning and Inference Research team turns these opportunities into tangible benefits for our members and our business.

The Machine Learning and Inference Research team is a dedicated research team building up Netflix’s technical capabilities by tackling fundamental research questions tied to our most important challenges and partnering closely with teams across the business to translate research into impact at scale. As a member of the team, you will leverage your technical expertise to shape roadmaps, collaborate across functions, and bring new ideas from exploration to impact. You will also engage actively with the broader research community by publishing at top venues, presenting at conferences, mentoring interns, and fostering academic collaborations.

We are seeking an early-career researcher who can grow to define and execute a strong research agenda with both internal and external visibility, disseminate knowledge effectively and inspire others, collaborate with colleagues to deliver tangible impact, and help foster an open environment of innovation, intellectual rigor, and curiosity.

What you bring

  • Ph.D. in Computer Science or a related field with a specialization in post-training LLMs for downstream tasks, especially using RL (e.g., RLVR, RLHF, offline or online, policy- or value-based), and possibly also including reasoning, alignment, distillation/compression, tool use, memory, calibration, or related.

  • A track record of top-tier publications demonstrating deep expertise in the specialization.

  • Passion for collaboration and for building strong relationships to tackle big, cross-functional problems.

  • Strong technical communication skills, with the ability to adapt to different audiences.

  • Self-motivated with an ability to thrive and to lead with minimal oversight and process.

  • Curiosity and judgment in identifying and framing ambiguous research and business problems, and connecting the two.

  • Eagerness to elevate the broader organization through sharing knowledge and guiding the adoption of new methods.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity 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.

Other facts

Tech stack
Machine Learning,Inference Research,Post-Training LLMs,Reinforcement Learning,Collaboration,Technical Communication,Self-Motivation,Curiosity,Knowledge Sharing,Research,AI,Data Analysis,Problem Solving,Mentoring,Academic Collaboration,Innovation

About Netflix

Netflix is one of the world's leading entertainment services, with over 300 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.

Team size: 10,001+ employees
LinkedIn: Visit
Industry: Entertainment Providers
Founding Year: 1997

What you'll do

  • As a member of the Machine Learning and Inference Research team, you will leverage your technical expertise to shape roadmaps and collaborate across functions. You will also engage with the broader research community by publishing, presenting, and mentoring.

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Frequently Asked Questions

What does a Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) do at Netflix?

As a Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) at Netflix, you will: as a member of the Machine Learning and Inference Research team, you will leverage your technical expertise to shape roadmaps and collaborate across functions. You will also engage with the broader research community by publishing, presenting, and mentoring..

Why join Netflix as a Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training)?

Netflix is a leading Entertainment Providers company.

Is the Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) position at Netflix remote?

The Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) position at Netflix is based in New York, United States and Los Gatos, California, United States. Contact the company through Clera for specific work arrangement details.

How do I apply for the Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) position at Netflix?

You can apply for the Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training) position at Netflix directly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process. You can also learn more about Netflix on their website.