Engineering Manager - Offline Inference - Machine Learning Platform

January 20

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Netflix

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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!

10,000+ employees

Founded 1997

👥 B2C

🛍️ eCommerce

📱 Media

📋 Description

• Netflix is one of the world's leading entertainment services. • The Offline Inference team builds and maintains the infrastructure enabling ML practitioners to run large-scale offline batch inference workflows. • We are looking for an experienced ML/AI infrastructure engineering leader to lead the development of the next-generation offline inference platform. • You will lead this newly formed team to architect, design, develop, test, and launch a brand-new platform. • You will be highly cross-functional in partnering with other engineering, product management, machine learning, and data teams. • To succeed in this role, you will need a strong ML infrastructure background and a passion for building scalable, robust systems.

🎯 Requirements

• 10+ years of software engineering experience and 3+ years of management experience. • Experience leading teams responsible for building high-traffic distributed systems and ML infrastructure • Experience with containerization and orchestration technologies to support data preparation, processing, and inference for large-scale ML models. • A proven understanding of ML frameworks and commercial ML/AI infrastructure, such as PyTorch, SageMaker, Ray Serve, and HuggingFace. • Strong technical acumen and can act as a credible technical advisor to the team, set and enforce a high-quality bar for code and system design, and be a mentor for the team. • A passion for translating the needs of ML practitioners into infrastructure offerings with an eye toward automated and self-serve capabilities. • Strong communication and collaboration skills and ability to build strong relationships with internal customers and external partners. • A demonstrated ability to develop, drive, and execute a technical vision and roadmap. • A track record of attracting top talent and leading and growing high-performance, diverse, and highly talented tenured engineers deep into their careers to maximize their impact and deliver results in a fast-paced and dynamic environment. • Experience managing a hybrid team with partners and team members distributed across (US) geographies & time zones.