Machine Learning Engineer 5 - Ads Inventory Management & Forecasting

Netflix, Inc.; Los Gatos (CA); On-site; USD 466,000 - 750,000; Full time

Benefits offered by this job

Comprehensive health plans

401k retirement plan with employer match

Stock option program

Disability programs

Flexible spending accounts

Paid leave of absence programs

Job summary

Netflix, Inc. is seeking an experienced individual to build end-to-end ML model deployment infrastructure for low-latency real-time advertising systems. Responsibilities include handling large volumes of data and productionizing models for campaign effectiveness. Salary ranges from $466,000 to $750,000, reflecting candidate expertise and market indicators.

The role offers comprehensive benefits, including health plans, life and serious injury benefits, stock options, and more.

Qualifications

• Experience in building ML model deployment and inference infrastructure for low-latency real-time ad systems.
• Experience handling large volumes of data with big-data tools like Spark.
• Experience with productionizing predictive models for advertising campaign effectiveness.

Responsibilities

• Build end-to-end ML model deployment and inference infrastructure for real-time advertising systems.
• Handle data at large volumes with big-data tools.
• Productionize predictive models for advertising campaign effectiveness.

Skills

Building ML model deployment infrastructure

Handling large data with Spark

Productionizing predictive models

Building simulation solutions for inventory forecasting

Understanding advertising marketplace

Lucene indexing

Familiarity with ad tech systems

Industry standards contribution (VAST, OpenRTB)

Legal compliance in ad-tech

Experience in CTV space

Tools

Spark

Job description

Job Overview

Ads Platform Engineering teams build advertising systems and integrations that power the delivery of ads using Netflix’s content delivery ecosystem. The Ads Inventory Management & Forecasting team builds real‑time inventory forecasting solutions leveraging ML models and high‑performance ad server simulations, and supports publisher inventory management solutions such as dynamic pricing, rate‑card management, product packaging, inventory split, and yield optimization.

Responsibilities

• Build end‑to‑end ML model deployment and inference infrastructure for low‑latency real‑time advertising systems.
• Handle data at extremely large volumes with big‑data tools like Spark.
• Productionize predictive models that forecast the effectiveness of advertising campaigns, including metrics such as impressions, reach, clicks, conversions, and ROI.
• Build scalable simulation solutions to model different inventory scenarios, including demand fluctuations, pricing strategies, and inventory allocation.
• Collaborate with cross‑functional stakeholders—including science, product, engineering, operations, design, and consumer research—to productionize and deploy models at scale.

Core Skills & Experience

• Experience in building end‑to‑end ML model deployment and inference infra for low‑latency real‑time ad systems.
• Experience handling large volumes of data with big‑data tools like Spark.
• Experience with productionizing predictive models for advertising campaign effectiveness.
• Experience building scalable simulation solutions for inventory forecasting.
• General understanding of the advertising marketplace and publisher‑side challenges such as fill‑rate optimization and revenue maximization.
• Experience with Lucene indexing on large volumes of data (nice to have).
• Familiarity with publisher‑side ad tech systems (ad servers, bidders, yield optimizers, SSPs/DSPs) and dynamic allocation of guaranteed and non‑guaranteed inventory (nice to have).
• Experience contributing to industry standards such as VAST or OpenRTB (nice to have).
• Familiarity with legal compliance and ad‑tech regulations worldwide (nice to have).
• Experience working in the CTV space and understanding its constraints (nice to have).

Compensation & Benefits

The compensation structure for this role consists solely of an annual salary with no bonuses. Salary is determined by market indicators and the candidate’s background, skills, and experience and ranges from $466,000 to $750,000. Netflix provides comprehensive benefits including health plans, mental health support, a 401k retirement plan with employer match, stock option program, disability programs, health savings account, flexible spending accounts, family‑forming benefits, life and serious injury benefits, and paid leave of absence programs.

EEO Statement

Netflix is an equal‑opportunity employer and celebrates diversity, recognizing that diversity builds stronger teams. 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.