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 experienced researcher who can establish and execute a strong research agenda in AI alignment science, pursue both internal and external impact, disseminate knowledge effectively and inspire others, collaborate with colleagues to deliver tangible business value, and help foster an open environment of innovation, intellectual rigor, and curiosity. This role will pursue frontier, foundational research that shapes the direction of the field and influences how Netflix develops and applies advanced AI systems across internal workflows and member-facing products.
What you bringTrack record of research excellence in the post-training and alignment of foundation models and agentic systems, with expertise in areas such as reinforcement learning, preference optimization and reward modeling, reasoning and test-time inference, model distillation, agent scaffolding and evaluation, multi-agent systems, memory and long-horizon interaction, calibration and uncertainty, interpretability, robustness, or safety.
Ph.D. in a relevant area, with at least 2 years of post-Ph.D. experience in industry and/or academia.
Experience in applying research (especially your own) to transform real-world problems in collaboration with engineering and business teams.
Extensive research experience, in industry and/or academia, including as evidenced in top-tier publications.
Recognized for both technical expertise and the impact you drive, and trusted by stakeholders for collaboration, guidance, problem‑solving, and decision‑making.
Excellent judgment in identifying and framing ambiguous research and business problems and the links between the two.
Demonstrated ability to collaborate and build strong working relationships with colleagues and stakeholders to tackle big, cross-functional problems.
Effective communication with technical, non-technical, and mixed audiences.
Able to operate autonomously, take ownership in environments with minimal oversight, and lead work effectively with lightweight processes.
Uplevels the greater org through sharing knowledge and guiding thought on the adoption of new methods. Actively mentors others and is sought out as a mentor.
Netflix has a unique culture and environment. Learn more here.
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.
Skills Required
- Ph.D. in a relevant field
- At least 2 years of post-Ph.D. experience in industry and/or academia
- Research excellence in post-training and alignment of foundation models and agentic systems
- Expertise in areas such as reinforcement learning, preference optimization, reward modeling, reasoning, test-time inference, model distillation, agent scaffolding, evaluation, multi-agent systems, memory, calibration, interpretability, robustness, or safety
- Extensive research experience demonstrated through top-tier publications
- Experience applying research to real-world problems with engineering and business teams
- Ability to identify and frame ambiguous research and business problems
- Strong cross-functional collaboration and stakeholder relationship-building skills
- Effective communication with technical, non-technical, and mixed audiences
- Ability to operate autonomously and lead work with minimal oversight
- Ability to mentor others and guide adoption of new methods
Netflix Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.
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Fair & Transparent Compensation — Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
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Equity Value & Accessibility — Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
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Healthcare Strength — Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.
Netflix Insights
What We Do
Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.






