Machine Learning Scientist - Live Ads

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.

We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.

Our Team

The Ad Supply & Decisioning team within the Ads Data Science and Engineering (DSE) organization drives ads growth by expanding ad inventory, optimizing member-ad matching, and maximizing long-term yield. The team spans three pillars, Ad Forecasting, Ad Ranking, and Ad Marketplace, and supports all ad surfaces, including live events such as sports, award shows, and cultural moments watched simultaneously by tens of millions of members around the world. Live advertising introduces a distinct class of problems: massive, unpredictable traffic spikes, global simultaneous delivery, hard real-time latency constraints, and the need to balance yield across direct and programmatic demand channels.

We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our core Live Ads ML problem areas - forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization. In this role, you will partner directly with the Live Ads product team to define the ML technical roadmap and collaborate across horizontal pods within Ad Supply & Decisioning to drive solutions.

Responsibilities

• Define and drive the ML technical roadmap in close partnership with the Live Ads product team, aligning technical investments with business priorities and product direction.

• Collaborate across horizontal pods to architect and deliver ML solutions spanning forecasting, targeting and personalization, bidding and pacing, auction, and yield optimization.

• Design and implement machine learning and optimization algorithms to improve ad quality and performance.

• Build, train, and evaluate models on large-scale production data.

• Develop online and offline evaluation frameworks to rigorously measure the impact of model and algorithm improvements.

• Partner closely with the product team to define optimization objectives, constraints, and trade-offs that align with product and business goals.

• Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, including senior leadership.

Qualifications

• Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field.

• 7+ years of industry experience building and shipping production ML systems at scale, with demonstrated staff/senior staff-level scope and impact.

• Deep knowledge of machine learning, optimization, and data analysis techniques.

• Experience in ad optimization stack, e.g. targeting, ranking, bidding. Experience in Live ads is a huge plus.

• Proven ability to set technical direction and influence roadmap across teams; experience serving as a vertical or staff-level technical lead is a strong plus.

• Experience with prototyping and deploying algorithms using large-scale production data.

• Proficiency in Python, Scala, or Java.

• Strong business acumen and ability to translate technical results into business impact.

• Excellent communication and collaboration skills.

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 $600,000.00 - $1,066,000.00. 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.