Machine Learning Engineer - Senior

February 10

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

💵 $100k - $720k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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Netflix

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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.

Revolutionizing the way people watch TV shows and movies!

10,000+ employees

Founded 1997

👥 B2C

🛍️ eCommerce

📱 Media

📋 Description

• Netflix is one of the world's leading entertainment services. • We build advertising systems and integrations that powers the delivery of ads. • Ads Inventory Management & Forecasting team builds state-of-art realtime inventory forecasting solution leveraging ML models. • 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 • Good understanding of Lucene index and had experience building Lucene index with large volume of data. • Familiar with publisher-side ad tech systems including ad servers, bidders, yield optimizers, and their demand-side counterparts (SSPs/DSPs) • Experience in yield optimization, product recommendation and dynamic allocation of direct/programmatic guaranteed and non-guaranteed inventory • Contributed to an ads industry technology standard (e.g VAST, OpenRTB) or worked on an industry consortium effort, working group etc. • Familiarity with legal compliance and changing landscape of ads regulations around the world. • Experience working in the CTV space and knowledge of its unique constraints

🏖️ 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 for full-time hourly employees • Flexible time off immediately entitled for full-time salaried employees