Software Engineer L4/L5 Training Platform, Machine Learning Platform

Company: Netflix

Location: Location not specified (Remote)

Type: Full-time

Level: mid

Remote: Yes

Posted: 2026-03-11

About this role

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.


Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.


**The Opportunity
We are looking for a driven Software Engineer to join the Training Platform team under our Machine Learning Platform (MLP) org. MLP’s charter is to maximize the business impact of all ML use cases at Netflix through highly reliable and flexible ML tooling and infrastructure that supports key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others.


In This Role You Will Get To**

  • Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company
  • Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training
  • Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform

Minimum Job Qualifications

  • Experience in ML engineering on production systems dealing with training or inference of deep learning models.
  • Proven track record of building and operating large-scale infrastructure for machine learn...

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