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 CVML Engineer - Body Technologies - Cupertino, California, United States

Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Creative services/Design
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200196933 / Latpro-3757071 
Date posted: Oct-07-2020
State, Zip: California, 95014


CVML Engineer - Body Technologies

Santa Clara Valley (Cupertino) , California , United States

Machine Learning and AI


Posted: Oct 6, 2020

Weekly Hours: 40

Role Number: 200196933

Have you devised breakthrough CV/ML algorithms to long-standing computer vision problems? Are you ready to collaborate with a Apple teams to bring your knowledge to market and make a far-reaching impact? We are looking for a driven computer vision engineer with a strong technical track record in computer vision for topics like multi-view geometry, shape fitting, key-point detection, people tracking, action classification or segmentation. You need to have a strong interest in solving real problems where developing and implementing algorithms are important parts. As a member of a small, dynamic team, you have the rare and rewarding opportunity to shape upcoming products that will delight and inspire millions of people every day.

Key Qualifications

  • Strong knowledge and experience in machine learning or classical computer vision
  • Experience working with real world data - big, messy, incomplete, full of errors
  • Strong mathematical foundation in computer vision and optimisation approaches
  • Solid mathematical foundation of machine learning techniques
  • Experience with collecting 2D / 3D data in the field and designing ground truth benchmarks
  • Experience in the field, proven by publications or a track record of successful projects
  • Strong experience in Python and C/C++
  • Passion for cutting edge computer vision / machine learning technologies and product delivery
  • Excellent understanding of data structures and algorithms
  • Excellent problem solving skills
  • Excellent verbal and written communication
  • Beneficial: Experience in processing working with large-scale datasets, capturing motion of deformable objects, semantic video analysis, high-framerate dense 3D reconstruction, photogrammetry, multimodal learning, animation, 3D computer graphics, algorithm optimization on CPU/GPU, HW-accelerated image or geometry processing, parallel compute architectures, asynchronous processing or embedded systems.


The Video Computer Vision (VCV) group delivers algorithms that drive revolutionary Apple products. We are the team that is responsible for many of the key algorithms for videos and photos on Apple products (e.g iPhone, iPad and more), provide backbone algorithms for ARKit, and conduct research and development in the space of Virtual and Augmented Reality. VCV's Body Technologies team develops people understanding algorithms that drive features such as ARKit Motion Capture. We are looking for smart researchers and engineers who are passionate about building products for millions of customers around the world. You will be working on ground breaking technology and develop algorithms that enable a high-quality user experience across a range of applications. As a part of our team, you will collaborate with both software teams (computer graphics, video engineering, data generation/annotation, system integration) and hardware engineers (cameras, silicon, electrical engineering, product design). Join us for the rare opportunity to work on novel algorithms software that go beyond the state of the art and eventually will touch the lives of millions of people around the world!

Education & Experience

PhD or MS in CS or similar. Alternatively, a comparable industry career with a proven track record.


See job description


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