Machine Learning Infrastructure Engineer

Company: Apple US Corp
Location: Cupertino, California, United States
Type: Full-time
Posted: 18.JUL.2021

Summary

SummarySummaryPosted: Apr 19, 2021 Role Number:Apple is looking for Machine Learning/Deep Learning infrastructure engineers to develop infra...

Description

SummarySummaryPosted: Apr 19, 2021 Role Number:Apple is looking for Machine Learning/Deep Learning infrastructure engineers to develop infrastructure for various ML/DL applications. Your work will enable researchers and engineers to build production ML/DL models at scale. Join Apple and help us leave the world better than we found it!WHAT YOU'LL DO- Develop highly scalable and reliable machine learning infrastructure that can perform model training and evaluation on a massive scale.- Build vital tools and infrastructure to monitor and understand the performance of complex systems.- Support the team to deploy models in a mission critical environment.Key QualificationsStrong background in building scalable and fault-tolerant distributed systems. Ideal candidates have past experience in building applications such as data pipelines, data caching/storage systems, and/or RPC services.Strong programming background, with extensive experience in Python. Experience with C++ is a plus.Familiarities with gRPC, ML model deployments, Ray, Spark, full-stack web developments are a plus.Previous experience with developing machine learning infrastructure or experience in using GPUs is a plus.DescriptionYou'll join a phenomenal team of hardworking engineers and researchers with deep experience in robotics, machine learning, and software engineering. We hope you're excited about the values that drive us:- Passion for the mission: We're here to make something great. We take on whatever work is right for the product and strive for the best possible results.- Modesty: The right answer is more important than being right. We search for solutions as a team and value clear-eyed feedback.- Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make great decisions.Education & ExperienceBachelors, Masters, or PhD Degree in Computer Science or equivalent professional experience.Additional Requirements

 
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