Machine Learning Engineer 5 – Ads Signals, Targeting

🕒 Yesterday

🇺🇸 United States – Remote

💵 $466k - $750k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Netflix

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1997

📱 Media

👥 B2C

Media • B2C

Netflix is a global streaming entertainment company and content producer whose stated mission is "to entertain the world. " It operates a consumer-facing subscription platform offering on-demand TV shows, films, and original programming, and also runs a public careers site emphasizing culture, inclusion, and hiring accommodations. The provided text highlights Netflix’s focus on recruiting talent worldwide, its work-life and culture pages, and its public-facing employer materials.

📋 Description

• Build end-to-end ML model deployment and inference infrastructure for low-latency real-time advertising systems • Build machine learning models for ads targeting and lookalike expansion • Design and build user and contextual signals and audience-targeting features for ad platforms • Handle extremely large data volumes using big data tools such as Spark • Collaborate with science, product, engineering, operations, design, and consumer research stakeholders • Productionize and deploy models at scale • Help build highly performant advertising systems that monetize Netflix content and deliver advertiser outcomes • Uphold member privacy and ensure relevant, appropriate, and brand-safe ads

🎯 Requirements

• Experience in building end-to-end ML model deployment and inference infrastructure for low-latency real-time ad systems • Experience building machine learning models for ads targeting and lookalike expansion • Professional experience designing and building user and contextual signals and audience targeting features for ad platforms • Proficiency in Java, C++, Python, or Scala • Solid understanding of multi-threading and memory management • Experience handling data at extremely large volumes with big data tools such as Spark • Strong understanding of data privacy, governance, and security concepts, including Privacy by Design principles • Experience with ads targeting using machine learning models • 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 • Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off • Full-time salaried employees are immediately entitled to flexible time off • Choice each year of compensation allocation between salary and stock options