Machine Learning Scientist 5 - 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 Core Ads Algorithms team is the engine behind the intelligence that powers ad personalization at Netflix. Our mission is to develop innovative, data-driven solutions that deliver highly relevant ad experiences to our members and drive impactful results for advertisers—all while maintaining the exceptional quality and personalization that define the Netflix experience. #

Responsibilities:

• Design and implement machine learning-driven bidding algorithms that optimize ad performance against objectives such as Clicks, Conversions, CPA and ROAS,.
• Build, train, and evaluate bidding algorithms on large-scale production data, ensuring robustness to marketplace dynamics, seasonality, and distribution shifts.
• Develop online and offline evaluation frameworks to rigorously measure the impact of bidding algorithms and policy changes.
• Inform and influence auction and pricing mechanism design, ensuring alignment between bidding algorithms, marketplace efficiency, and business goals.
• Partner closely with the product team to define bidding objectives, constraints, and trade-offs that align with product and revenue goals.
• Communicate technical decisions, trade-offs, and experiment results to both technical and non-technical stakeholders, driving understanding and adoption of ML-driven bidding solutions.

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Qualifications:

• Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or related quantitative field.
• Proficiency in Python, Scala or Java.
• Deep knowledge of machine learning, optimization, and data analysis techniques.
• Experience with prototyping and deploying algorithms using large-scale production data.
• Strong business acumen and ability to translate technical results into business impact.
• Experience in building bidding algorithms.
• 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 $466,000.00 - $750,000.00. 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.