Software Engineer, Training Platform, Machine Learning Platform

January 9

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Logo of Netflix

Netflix

Netflix is a global streaming service that offers a wide variety of award-winning television shows, movies, anime, documentaries, and more on thousands of internet-connected devices. It allows users to watch instantly and provides original content produced by Netflix itself, catering to diverse tastes. As a pioneer in original programming since its first series in 2013, Netflix aims to entertain audiences worldwide through immersive storytelling and innovative technology.

Revolutionizing the way people watch TV shows and movies!

πŸ“‹ Description

β€’ Design and build the platform that powers large-scale machine learning model training, fine-tuning, and evaluations workflows. β€’ Co-design and optimize systems and models for cost-effectiveness of machine learning model training. β€’ Design easy-to-use APIs and interfaces for experienced ML practitioners and non-experts.

🎯 Requirements

β€’ Experience in ML engineering on production systems dealing with training or inference of deep learning models. β€’ Proven track record of building and operating large-scale infrastructure for machine learning use cases. β€’ Experience with cloud computing providers, preferably AWS. β€’ Comfortable with ambiguity and working across multiple layers of the tech stack. β€’ Adopt and promote best practices in operations, including observability and logging. β€’ Excellent written and verbal communication skills. β€’ Comfortable working in a team with peers and partners distributed across geographies & time zones.

πŸ–οΈ Benefits

β€’ Health Plans β€’ Mental Health support β€’ 401(k) Retirement Plan with employer match β€’ Stock Option Program β€’ Disability Programs β€’ Health Savings and Flexible Spending Accounts β€’ Family-forming benefits β€’ Life and Serious Injury Benefits β€’ Paid leave of absence programs β€’ 35 days annually for paid time off for full-time hourly employees β€’ Immediate flexible time off for full-time salaried employees

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