Senior ML DNN Engineer, Perception


Posted: Nov 2, 2018

Weekly Hours: 40

Role Number: 200007261

Apple is looking for a talented, dedicated, and results-oriented DNN machine learning engineer to develop and integrate complex autonomous systems. In this position, you will have the opportunity to work with a multi-functional team on an innovative multi-platform hardware/software product.

Key Qualifications

  • 3+ years of Deep learning for vision/perception domain
  • 3+ years production software experience, especially collaboration with moderate to large groups of developers
  • Highly experienced with ML tools and libraries (Tensorflow/Pytorch)
  • Strong background in Python, C++, Linux
  • Experience with modern distributed computed paradigms and platforms (AWS. MapReduce, Spark)
  • Solid and fluent understanding of algorithm and data structures
  • Demonstrated creative, critical and independent thinking capabilities and troubleshooting skills.
  • Strong analytical and communication skills


You will design and develop state of the art DNN models for addressing complex perception tasks for an autonomous technology project. You will be concerned with the full stack of DNN development: designing and training DNN networks, write production code, develop tools and metrics for enabling DNNs on device and in production.

Education & Experience

Bachelor degree or Masters in computer science/ML equivalent professional experience.

Additional Requirements

  • - Passion for building great software
  • - Passion for clean APIs, and great documentation
  • - Passion for metrics and algorithm visualization
  • - Deployment of Deep Learning or ML models at scale or into production
  • - SQL and databases
  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants.

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