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Machine Learning Infrastructure Engineer
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Scala
  • Redis
  • Deep Learning
Apple
Santa Clara Valley, CA 95014
136 days ago

Summary

Posted: Jun 9, 2020Role Number:200174899Apple 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 Qualifications
  • Strong 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.
  • Substantial experience with multiple technologies from the following list: Arrow, Bazel, Docker, Kibana, MPI, MySQL, Redis, Spark, Zookeeper.
  • Ability to build full-stack web applications/services for internal tooling.
  • 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.

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