Netflix

5 months ago

Machine Learning Engineer 5 - Ads Inventory Management & Forecasting

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Build and deploy low-latency ML models that power Netflix’s ad-supported experience, focusing on ads inventory management and real-time forecasting. Develop large-scale predictive systems and simulation tools to model inventory scenarios, demand fluctuations, and pricing strategies. Partner with cross-functional teams to productionize and deploy models at scale, improving publisher monetization outcomes such as fill rates and revenue optimization.

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and implement ML inference and deployment infrastructure for low-latency real-time ad systems.
•Create forecasting models to predict advertising campaign effectiveness and related performance metrics.
•Develop systems for publisher inventory management supporting monetization strategies such as dynamic pricing and yield optimization.
•Build scalable simulations to evaluate different inventory scenarios, including demand changes and pricing strategies.
•Collaborate with science, product, engineering, operations, design, and consumer research teams to deploy models at scale.

Pay and Benefits

Salary: USD 466,000 - 750,000 annually

Perks:Health Insurance401kEquityPaid LeaveDisabilityLife InsuranceFlexible Spending

Key Requirements

•Build and deploy end-to-end ML model inference infrastructure for low-latency, real-time ad systems.
•Handle extremely large data volumes using big data tools such as Spark.
•Develop productionized predictive models to forecast advertising effectiveness metrics (e.g., impressions, reach, clicks, conversions, ROI).
•Build scalable simulation solutions to model inventory scenarios such as demand fluctuations, pricing strategies, and inventory allocation.
•Understand the advertising marketplace, with focus on publisher-side inventory management challenges like optimizing fill rates and maximizing revenue.

Experience:AdvertisingReal-time systemsBig dataConnected TV (CTV)Ad techProgrammatic advertising

Skills:CollaborationCross-functional teamwork

Tech Stack:Machine learningSparkLuceneAd serversSSPsDSPsYield optimizersVASTOpenRTBSimulation models

Company Brief

Netflix

Global subscription streaming service that produces and distributes movies, TV series, and games across multiple devices, operating worldwide with extensive original content and localized offerings.

Industry: Streaming Platforms

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Los Gatos, United States

Founded: 1997

Glassdoor: 4.1

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

Netflix

5 months ago

Machine Learning Engineer 5 - Ads Inventory Management & Forecasting

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and implement ML inference and deployment infrastructure for low-latency real-time ad systems.
•Create forecasting models to predict advertising campaign effectiveness and related performance metrics.
•Develop systems for publisher inventory management supporting monetization strategies such as dynamic pricing and yield optimization.
•Build scalable simulations to evaluate different inventory scenarios, including demand changes and pricing strategies.
•Collaborate with science, product, engineering, operations, design, and consumer research teams to deploy models at scale.

Pay and Benefits

Salary: USD 466,000 - 750,000 annually

Perks:Health Insurance401kEquityPaid LeaveDisabilityLife InsuranceFlexible Spending

Key Requirements

•Build and deploy end-to-end ML model inference infrastructure for low-latency, real-time ad systems.
•Handle extremely large data volumes using big data tools such as Spark.
•Develop productionized predictive models to forecast advertising effectiveness metrics (e.g., impressions, reach, clicks, conversions, ROI).
•Build scalable simulation solutions to model inventory scenarios such as demand fluctuations, pricing strategies, and inventory allocation.
•Understand the advertising marketplace, with focus on publisher-side inventory management challenges like optimizing fill rates and maximizing revenue.

Experience:AdvertisingReal-time systemsBig dataConnected TV (CTV)Ad techProgrammatic advertising

Skills:CollaborationCross-functional teamwork

Tech Stack:Machine learningSparkLuceneAd serversSSPsDSPsYield optimizersVASTOpenRTBSimulation models

Company Brief

Netflix

Global subscription streaming service that produces and distributes movies, TV series, and games across multiple devices, operating worldwide with extensive original content and localized offerings.

Industry: Streaming Platforms

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Los Gatos, United States

Founded: 1997

Glassdoor: 4.1

Website LinkedIn Glassdoor