Machine Learning Scientist 5 - Sales, Ads DSE

Netflix is hiring a Machine Learning Scientist 5 to lead machine learning for sales productivity and automation within its Ads Data Science & Engineering organization. This is a senior, individual-contributor role for someone who can find the highest-leverage places for AI to improve how Netflix's ad sales team works, then build those systems end to end. You would sit in the Sales pod of the Demand Science team and work closely with Product Managers, Engineers, and Sales stakeholders.

The Demand Science team supports Netflix Ads growth by helping the business attract, activate, and scale advertiser demand. The goal for this role is to help sellers work smarter, close more deals, and grow Ads revenue without growing headcount at the same pace.

What you will do

• Define the AI/ML investment roadmap for the Sales pod with product and engineering partners, identifying where data science can most improve sales productivity and revenue outcomes.
• Design, build, and deploy production ML models, AI agents, and automation systems end to end.
• Work with Analytics Engineers to build the metrics, measurement pipelines, and reporting that guide investment decisions and track product performance.
• Iterate on launched products using performance data and seller feedback, with attention to measurable business impact.
• Serve as a senior technical voice in cross-functional discussions, communicating with both technical and non-technical stakeholders.

Where the work focuses

• Workflow automation: With Product, identify and automate high-friction points in the sales workflow to reduce delays, cut manual work, and improve accuracy, so sellers spend less time on process and more time selling.
• AI-augmented selling: Design and deploy AI agents and assistants that make selling faster and more effective, including helping sellers prepare for client conversations, respond to RFPs, and close higher-value deals more quickly.

What they are looking for

• An advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.
• A track record of independently scoping and leading end-to-end ML projects in production, including identifying the right problems to solve and driving them from idea to measurable impact.
• Strong strategic acumen: the ability to understand business objectives deeply and turn them into a prioritized technical roadmap.
• Comfort with ambiguity and a proactive, curious approach to problem-solving.
• Excellent communication with technical and non-technical audiences, plus the curiosity and user empathy to understand sales pain points.
• Proficiency in Python and SQL for building ML pipelines and models.
• Experience with LLMs, AI, or agentic systems is a bonus but not required. Netflix notes that candidates with strong ML product-building experience who are willing to learn into AI can also be successful here.
• Resonance with the Netflix Culture Memo.

Pay and benefits

The range for this role is $466,000.00 to $750,000.00 per year, and the range will vary based on location. Netflix's compensation structure consists solely of an annual salary, with no bonuses. Each year you choose how much of your compensation you want in salary versus stock options. Netflix says it relies on market indicators and considers your job family, background, skills, and experience to determine your compensation within the market range.

Benefits include health plans, mental health support, a 401(k) retirement plan with employer match, a stock option program, disability programs, health savings and flexible spending accounts, family-forming benefits, and life and serious injury benefits. Paid leave of absence programs are also offered. Full-time hourly employees accrue 35 days annually for paid time off for vacation, holidays, and sick leave. Full-time salaried employees are immediately entitled to flexible time off.

Other details

The role is based in the United States. Netflix states it is an equal-opportunity employer and does 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. Candidates who need an accommodation or adjustment for a disability or any other reason during the hiring process can send a request to their recruiting partner. The job is open for no less than 7 days and will be removed when the position is filled.