15 days old

Deep Learning Engineer- Deformable Object Tracking

Cupertino, CA
  • Job Code
    200057293
Summary

Summary

Posted: May 1, 2019

Weekly Hours: 40

Role Number: 200057293

Have you previously devised breakthrough deep learning solutions to long-standing computer vision problems? Are you ready to collaborate with a talented team to bring your knowledge to market and make a far-reaching impact? The Technology Development Group delivers computer vision algorithms that drive revolutionary Apple products. We are targeting a driven and dedicated deep learning engineer with a strong technical track record in tracking of deformable objects. As a member of a small, fast-paced team, you have the unique and rewarding opportunity to shape upcoming products that will delight and inspire millions of people every day

Key Qualifications

  • Strong knowledge and experience in deep learning algorithms for tracking of non-rigid objects, deformable surfaces, or highly related applications
  • Experience working with real world data - big, messy, incomplete, full of errors
  • Strong mathematical foundation of machine learning / deep learning techniques
  • Solid mathematical foundation in computer vision
  • 3+ years of experience in the field, proven by publications or a track record of successful projects
  • Strong experience in Python and C/C++
  • Solid experience in at least one major machine learning framework: Caffe, TensorFlow, Torch, Theano, Keras, etc
  • Passion for cutting edge computer vision / machine learning technologies and product delivery
  • Excellent understanding of data structures and algorithms
  • Self motivated
  • Excellent problem solving skills
  • Excellent verbal and written communication
  • Beneficial: Experience in large-scale data capture campaigns, capturing ground-truth motion of deformable objects, real-time tracking algorithms, semantic video analysis, high-framerate dense 3D reconstruction, photogrammetry, multimodal learning, animation, 3D computer graphics, multiple view geometry, computational geometry, non-linear optimization, iOS programming, algorithm optimization on CPU/GPU, HW-accelerated image or geometry processing, parallel compute architectures, asynchronous processing or embedded systems

Description

We are the team that is responsible for many of the key algorithms within the Technology Development Group. We are looking for talented engineers who are passionate about building products for millions of customers around the world. You'll be working on cutting-edge technology and develop algorithms that enable a high-quality user experience across a range of tentpole use cases and applications. As a part of our team, you will closely collaborate with HW engineers (cameras, silicon, electrical engineering, product design) and other technology development software teams (computer graphics, video engineering, data generation/annotation, drivers/OS). You can make a difference by researching and prototyping novel deformable object tracking algorithms beyond the state of the art and/or by optimizing the performance of real-time algorithms running on Apple silicon

Education & Experience

PhD or Master of Science degree in Computer Science or similar
Alternatively, a comparable industry career with a proven track record
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.

Posted: 2019-11-02 Expires: 2019-12-01

Before you go...

Our free job seeker tools include alerts for new jobs, saving your favorites, optimized job matching, and more! Just enter your email below.

Share this job:

Deep Learning Engineer- Deformable Object Tracking

Apple, Inc.
Cupertino, CA

Join us to start saving your Favorite Jobs!

Sign In Create Account
Powered ByCareerCast