[Hiring] Machine Learning Engineer @Netflix

Role Description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

We launched a new ad-supported tier in November 2022 to offer our members more choice in how they consume their content. Our new tier allows us to attract new members at a lower price point, while also creating a compelling path for advertisers to reach audiences that are deeply engaged.

The Ads Platform Engineering teams build advertising systems and integrations that power the delivery of ads using our world-class content delivery ecosystem. We deliver ads in a manner that’s thoughtful of our member’s viewing experience and drive great outcomes for advertisers.

Our team is growing to meet ambitious goals: building highly performant advertising systems to effectively monetize our incredible slate of content and deliver real impact for the business.

The Ads Signals & Targeting team is revolutionizing ad experiences by utilizing advanced machine learning models for identity resolution and optimal behavioral and contextual audience targeting. We create foundational systems that deliver relevant and engaging ads to Netflix members, all while upholding their privacy.

We are looking for highly motivated engineers working in the advertising space who are excited to join us on this journey.

Qualifications

• Experience in building end-to-end ML model deployment and inference infra for low-latency real-time ad systems.
• Experience building machine learning models for ads targeting and lookalike expansion.
• Professional experience in designing and building user and contextual signals and audience targeting features for ad platforms.
• Proficiency in Java, C++, Python, or Scala with a solid understanding of multi-threading and memory management.
• Experience in handling data at extremely large volumes with big data tools like Spark.
• Collaborate with cross-functional stakeholders from the science team, product, engineering, operations, design, consumer research, etc., to productionize and deploy models at scale.

Requirements

• 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

• Comprehensive 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.