Machine Learning Scientist 5 - Sales, Ads DSE

About the Role

Netflix is hiring a senior machine learning scientist to support the Ads Data Science & Engineering organization. This role sits in the Demand Science team and focuses on helping the ads business grow by improving how advertiser demand is attracted, activated, and scaled. You will act as the ML lead for sales productivity and automation within the Sales pod, working closely with Product, Engineering, and Sales partners to find the biggest opportunities for AI and turn them into real products and systems.

The position is centered on using data science, machine learning, and AI to reduce friction in the sales process, help sellers work more efficiently, support higher-value deal closure, and enable ads revenue growth without a proportional increase in headcount.

Scope of Work

• Spot and remove bottlenecks in the sales workflow through automation and AI-enabled tools.
• Build assistants and agentic solutions that help with client preparation, RFP responses, and deal progression.
• Set the technical direction for sales productivity and automation initiatives in partnership with product and engineering.
• Deliver measurement frameworks, reporting, and analytics pipelines to evaluate outcomes and guide investment choices.
• Continuously improve shipped solutions using performance signals and feedback from sellers.
• Represent the technical perspective in cross-functional conversations with both technical and non-technical partners.

What You’ll Be Responsible For

• Creating the AI and ML roadmap for the Sales pod.
• Designing, building, and deploying production-ready ML models, automation workflows, and AI systems from start to finish.
• Collaborating with analytics engineers on metrics, experimentation, and product performance tracking.
• Translating business goals into a prioritized technical plan with measurable impact.
• Leading ambiguous problems independently and driving them to execution.

Candidate Profile

• You should hold a PhD or Master’s degree in Computer Science, Statistics, Mathematics, or another quantitative discipline.
• Experience leading end-to-end machine learning work in production is important, including problem framing, scoping, implementation, and impact measurement.
• You need strong business judgment and the ability to turn company goals into technical priorities.
• Comfort working through uncertainty and solving open-ended problems is essential.
• You must be able to communicate clearly with a range of stakeholders and understand sales pain points with empathy.
• Proficiency in Python and SQL is required for ML development and pipelines.
• Experience with LLMs, AI, or agent-based systems is helpful but not mandatory.
• Alignment with Netflix’s culture is expected.

Compensation and Benefits

The company states that compensation is structured as annual salary only, with no bonus. Employees may choose how much of their compensation is taken as salary versus stock options each year. The stated pay range for this role is between $466,000 and $750,000, and the final amount depends on location, job family, background, skills, and experience.

Netflix offers a broad benefits package that includes health coverage, mental health support, a 401(k) plan with employer match, a stock option program, disability programs, health savings and flexible spending accounts, family-forming benefits, life and serious injury benefits, and paid leave programs. Full-time hourly employees receive 35 days of paid time off per year for vacation, holidays, and sick leave. Full-time salaried employees receive flexible time off immediately.

Equal Opportunity and Hiring Process

Netflix says it is committed to inclusion and aims to provide a meaningful interview experience for all candidates. Candidates who need an accommodation or adjustment during the hiring process for a disability or any other reason should contact their recruiting partner. The company is an equal-opportunity employer and does not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Additional Information

The position is open for at least 7 days and will be taken down once filled.

This opportunity is based in the United States.