AI Research Scientist - Generative Models

At Netflix, our mission is to connect global stories with audiences worldwide. When a Netflix member opens our app, we have a few precious moments to help them choose a story or a game that is right for them at that instance. Presenting them evidence (e.g. Artwork, Trailers, Synopses) that authentically represents each title and resonates with the member is essential to this effort.

The Promotional Assets & Creative Technology AIMS team is at the forefront of Netflix's efforts to effectively promote titles and enhance the content discovery experience. Our team partners closely with Netflix's world-class creative writing teams to amplify and scale promotional writing for our members. We are looking for a seasoned Machine Learning Scientist to design and develop innovative Machine Learning (ML) solutions. In this rare opportunity, you will have the chance to define the direction for algorithmic strategies and spearhead the execution of ML solutions and ultimately shape how titles are promoted on Netflix and discovered by our members.

Responsibilities:

• Design rigorous experiments to test hypotheses, from setup through statistical validation — e.g., comparing two summary-generation algorithms with limited sample sizes, accounting for experimental limitations, and drawing sound conclusions.

• Translate complex technical concepts for both technical and non-technical stakeholders to inform strategic decisions.

• Lead end-to-end ML development: research, model training, and evaluation.

• Partner with ML scientists and engineers to integrate models into business applications and platforms.

• Act as a subject matter expert, working cross-functionally to identify high-impact opportunities and define and execute roadmaps.

• Track advancements in the field and apply them to improve the promotional writing experience for members.

• Engage with the ML community, internal and external, to learn, to teach, and to contribute to building a great Netflix brand.

About you:

• Track record of designing, running, and analyzing rigorous experiments — from hypothesis formation through statistical validation of results.

• Strong foundation in ML and Deep Learning, especially in Natural Language Processing / Understanding and Generation. Research experience in summarization or generated-text evaluation is a big plus; background in vision models such as diffusion models is a plus.

• Expertise in one or more LLM post-training approaches.

• Strong programming skills in Python, with experience in common ML/DL frameworks such as PyTorch or TensorFlow.

• PhD (preferred) or MSc in ML, Computer Science, or a related field.

• Proven track record of bringing clarity and leading ambitious roadmaps to solve complex problems.

• Exceptional communication and collaboration skills, and passionate about positively contributing to the team and company culture.

• Comfortable with ambiguity, able to take ownership, and able to thrive with minimal oversight or process.