Machine Learning Engineer 5 - Ads Platform Engineering

Netflix
United States
Workplace: OnsiteFull timeUSD 466,000 - 750,000 annuallyFunction: Data Science & Machine LearningSkills: ["Cross-functional collaboration"]

Build and productionize machine learning models that power Netflix’s ads platform, including real-time ad decisioning, inventory forecasting, scoring/bid ranking, and cost-per metrics optimization. Work across the Ads Platform Engineering teams to deploy low-latency inference and scalable systems handling massive data volumes. Collaborate with science, product, engineering, and operations partners to integrate advertising experiences and improve publisher outcomes while ensuring brand safety and privacy.

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FursaFursa
Netflix
Netflix
1 year ago

Machine Learning Engineer 5 - Ads Platform Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Build and productionize machine learning models that power Netflix’s ads platform, including real-time ad decisioning, inventory forecasting, scoring/bid ranking, and cost-per metrics optimization. Work across the Ads Platform Engineering teams to deploy low-latency inference and scalable systems handling massive data volumes. Collaborate with science, product, engineering, and operations partners to integrate advertising experiences and improve publisher outcomes while ensuring brand safety and privacy.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Build ML models and systems for ads inventory management and real-time inventory forecasting.
  • •Develop core ads serving models for low-latency decisioning and optimize campaign performance using budgeting, pacing, and dynamic allocation.
  • •Create interfaces and integrations for programmatic buying via selected SSPs and DSPs.
  • •Optimize ad formats and member experiences across Netflix clients using ad-serving infrastructure.
  • •Build audience and identity resolution capabilities using advanced ML while maintaining privacy and improving targeting outcomes at scale.

Pay and Benefits

Salary: USD 466,000 - 750,000 annually
Equity and Bonus:Equity
Perks:Health Insurance401kEquityDisabilityPaid LeaveLife Insurance

Key Requirements

  • •Proficiency in Java, C++, Python, or Scala with strong multi-threading and memory-management fundamentals.
  • •Experience building and deploying end-to-end ML model inference infrastructure for low-latency real-time ad systems.
  • •Experience handling extremely large-scale data using big data tools like Spark.
  • •Experience with yield optimization, scoring, bid ranking, and dynamic allocation across direct and programmatic inventory.
  • •Modeling and building predictive systems to optimize CPC/CPV/CPCV and forecast campaign effectiveness (impressions, reach, clicks, conversions, ROI).
Experience:AdvertisingMachine learningBig dataReal-time systemsCTV
Skills:Cross-functional collaboration
Tech Stack:JavaC++PythonScalaSparkLuceneVASTOpenRTBSSPsDSPsInventory forecastingAd server simulations

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
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