We use cookies. Find out more about it here. By continuing to browse this site you are agreeing to our use of cookies.

Job posting has expired

#alert
Back to search results

Machine Learning Engineer, Framework (Planning) - SPG

Apple, Inc.
United States, California, Cupertino
August 14, 2022
Summary
Posted: Mar 17, 2022
Role Number: 200358085
Apple is looking for Machine Learning engineers to develop ML frameworks for various robotics applications. Your work will directly enable researchers and engineers to build state-of-the-art ML models tackling extremely complex problems that can be deployed into the physical world. You'll join a fantastic team of world-class engineers and researchers with extensive experience and reputation in robotics and machine learning to work on very complex and exciting AI projects that could bring high impacts to society. We strive to develop innovative and industry-leading solutions for every challenging problem we work on.
Key Qualifications
  • Strong programming background, with extensive experiences in Python. Experience with C++ is a plus.
  • Background in building distributed systems, data pipelines, working with various cloud technologies.
  • Experience with developing large scale machine learning, reinforcement learning infrastructure is a plus.
  • Past experience in developing production DL models and familiarity with common DL frameworks is a plus.
  • A strong desire to learn new things and to become an expert at what you do.
Description
* Develop highly scalable, efficient, and flexible machine learning frameworks that can perform supervised/reinforcement learning on a massive scale. * Address short-comings and develop new features in our framework by directly working with and contributing to multiple production ML projects. * Build tools, pipelines or workflows to help facilitate the analysis, evaluation and the eventual deployment of highly complex ML models. * Build tools, pipelines and frameworks to efficiently scale ground truth data for various machine learning applications from real world data.
Education & Experience
Bachelors, Masters, or PhD Degree in Computer Science or equivalent professional experience.
Additional Requirements

(web-5bb4b78774-f7f6c)