[Hiring] Machine Learning Scientist @Netflix

Role Description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

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

• Track advancements in LLM and generative model research, and translate them into concrete opportunities for the problem space we are working on.
• Apply state-of-the-art techniques to high-impact problems such as summarization quality and building LLM-based evaluators ("judges") that assess whether generated content meets quality bars.
• Lead end-to-end ML development on these problems: research, model training, and evaluation.
• Partner with ML scientists and engineers to integrate models into business applications and platforms.
• Translate complex technical concepts for both technical and non-technical stakeholders to inform strategic decisions.
• Act as a subject matter expert, working cross-functionally to identify high-impact opportunities and define and execute roadmaps.
• Engage with the ML community, internal and external, to learn, to teach, and to contribute to building a great Netflix brand.

Qualifications

• Demonstrated habit of tracking the LLM/generative model literature and a knack for spotting which advances are relevant to real business problems.
• Strong foundation in ML and Deep Learning, especially in Natural Language Processing / Understanding and Generation.
• Research experience in summarization or generated-text evaluation (e.g., LLM-as-judge methods) is a big plus; background in vision models such as diffusion models is a plus.
• Expertise in one or more LLM post-training approaches.
• Track record of designing, running, and analyzing rigorous experiments — from hypothesis formation through statistical validation of results.

Requirements

• Generally, our compensation structure consists solely of an annual salary; we do not have bonuses.
• You choose each year how much of your compensation you want in salary versus stock options.
• The range for this role is $300,000.00 - $537,000.00. This compensation range will vary based on location.

Benefits

• Comprehensive Health Plans
• Mental Health support
• 401(k) Retirement Plan with employer match
• Stock Option Program
• Disability Programs
• Health Savings and Flexible Spending Accounts
• Family-forming benefits
• Life and Serious Injury Benefits
• Paid leave of absence programs
• Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.
• Full-time salaried employees are immediately entitled to flexible time off.