Research Scientist 6 - Machine Learning and Inference Research, AI Alignment Science

Netflix; Amsterdam; On-site; EUR 150,000 - 210,000; Full time

Job summary

Netflix is seeking an experienced Research Scientist 6 in Machine Learning and Inference Research to establish and execute a strong research agenda in AI alignment science. You will shape roadmaps, collaborate with cross-functional teams, and translate research into tangible business value for Netflix’s member experience.

You will publish findings at top venues, mentor interns, and engage with the broader research community while advancing frontier, foundational research that informs how Netflix

Qualifications

• PhD in a relevant area with 2+ years post-PhD experience.
• Track record in post-training alignment of foundation models.
• Ability to translate research into real-world impact with engineering/business teams.
• Strong collaboration and communication with diverse stakeholders.

Responsibilities

• Publish at top venues and present at conferences.
• Collaborate across functions to translate research into impact.
• Mentor interns and foster academic collaborations.
• Define roadmaps and drive research from exploration to impact.
• Lead with curiosity and foster open environment for innovation.

Skills

Foundation models

Reinforcement learning

Agentic systems

Research leadership

Publications

Cross-functional collaboration

Mentoring

Education

PhD in a relevant field

Tools

Python

ML frameworks

Job description

We are seeking an experienced researcher for the Research Scientist 6 - Machine Learning and Inference Research, AI Alignment Science role 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.

• Location: Amsterdam, Netherlands
• Work type: Onsite
• Team: Data & Insights

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.

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 bring

• Track 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.