The role
From Netflix's own posting.
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 Demand Science team within Ads Data Science & Engineering plays a crucial role in Netflix Ads growth by equipping the business to efficiently attract, activate, and scale advertiser demand. As a machine learning scientist in Media Planning, you'll work across the ML models and AI agents that turn advertiser briefs into optimized, ready-to-buy media plans. We're looking for a generalist who's curious, motivated to learn, and eager to build alongside the rest of the team, not someone who's already settled into one corner of ML.
What You'll Do:
Design and ship production ML models and conversational AI agents that parse advertiser requests and help sellers plan and compare media plan options.
Build and evolve the systems that evaluate and improve agent and model decision quality over time.
Partner with scientists and engineers across the media planning recommendation and agent workstreams to ship and iterate on new capabilities.
Dig into ambiguous problems, propose approaches, and drive them from idea to production.
Iterate on launched models and agents based on performance data and seller feedback.
Communicate clearly with both technical and non-technical stakeholders.
Nice to have:
Experience with operations research.
Experience with AI engineering or agentic systems.
Who You Are:
Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.
Experience building and shipping ML models or systems in production.
Curious and motivated to learn across ML domains, not attached to a single specialty.
Strong collaborator who's energized by building alongside others, not just independently.
Comfortable with ambiguity, able to take ownership with minimal oversight.
Proficient in Python and SQL.
Enthusiastic about and compatible with Netflix culture.
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. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer 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. See more details about our Benefits here .
Netflix is a unique culture and environment. Learn more here .
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do 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.
Job is open for no less than 7 days and will be removed when the position is filled.