ISE, SIML - Software Development Engineer in Test

Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI

Summary

Posted:
Role Number: 200105584
Job Summary The System Intelligent and Machine Learning Group at Apple is responsible for creating exciting technologies that enable Apple's products, such as Photo search, smart camera, Clips, ARKit, CoreML, Vision etc for OS X, watchOS, tvOS and iOS. The group combines research and development in a fast-paced environment. We’re looking for a flexible engineer who enjoys applying their skills to a wide variety of tasks. Strong analytical and problem solving abilities are paramount, as is a clear passion for writing quality code.

Key Qualifications

  • You are a strong and seasoned software development experience in scripting languages like, Python
  • You have experience with benchmark/test development and test automation
  • You have experience with building continuous integration systems/framework
  • You have a strong desire for ensuring released products are of the highest possible quality
  • You are familiarity with coding languages, e.g. C/C++
  • You are an effective communicator and love working closely with others
  • You are experience with OS X and/or iOS development and familiarity with UNIX-based

Description

In this role you will help take breakthrough computer vision and machine learning algorithms out of the labs, and put them into products used by millions of people on all Apple devices every day. You will help by providing the benchmarks and testing infrastructure to ensure algorithm quality meets expectations and does not regress. As an experienced software engineer you should have a passion for test development, automation, and benchmarking. You will be implementing benchmarks to track the performance of computer vision and machine learning algorithms. You will define the benchmark, gather the required data, develop the benchmark, run it on an automated system and monitor the results.

Education & Experience

Bachelor’s or Master’s in Computer Science, Computer Engineering, Computer Learning, or Electrical Engineering or equivalent

Additional Requirements