Machine Learning Engineer - Senior

April 10

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Netflix

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B2C • eCommerce • Media

Netflix is a global streaming service that offers a wide variety of award-winning television shows, movies, anime, documentaries, and more on thousands of internet-connected devices. It allows users to watch instantly and provides original content produced by Netflix itself, catering to diverse tastes. As a pioneer in original programming since its first series in 2013, Netflix aims to entertain audiences worldwide through immersive storytelling and innovative technology.

- employees

Founded 1997

👥 B2C

🛍️ eCommerce

📱 Media

💰 $20M Post-IPO Equity on 2022-01

📋 Description

• Netflix is one of the world's leading entertainment services with 283 million paid memberships in over 190 countries. • The Ads Platform Engineering teams build advertising systems and integrations that power the delivery of ads. • The Ads Inventory Management & Forecasting team builds state-of-the-art realtime inventory forecasting solutions leveraging ML models and high performance ad server simulations. • As one of the newest entrants in the Connected TV advertising space, we seek to build unique value propositions that help us differentiate from the competition.

🎯 Requirements

• Experience in building end-to-end ML model deployment and inference infra for low-latency real-time ad systems. • Experience in handling data at extremely large volumes with big data tools like Spark. • Productionized predictive models to forecast the effectiveness of advertising campaigns, including metrics like impressions, reach, clicks, conversions, and ROI. • Building Scalable Simulation solution to model different inventory scenarios, including demand fluctuations, pricing strategies, and inventory allocation. • Familiar with ads budgeting and pacing systems, models, and algorithms. • General understanding of the advertising marketplace and landscape, with a focus on publisher side challenges like optimizing fill rates and maximizing revenue in the context of inventory management. • Collaborate with cross-functional stakeholders from science team, product, engineering, operations, design, consumer research, etc., to productionize and deploy models at scale.

🏖️ Benefits

• Health Plans • Mental Health support • 401(k) Retirement Plan with employer match • Stock Option Program • Disability Programs • Health Savings and Flexible Spending Accounts • Family-forming benefits • Life and Serious Injury Benefits • Paid leave of absence programs • 35 days annually for paid time off (full-time hourly employees) • Flexible time off (full-time salaried employees)