Apple AR/VR Job | CVML Engineer – Activity Recognition (TDG)
Job（岗位）: CVML Engineer – Activity Recognition (TDG)
Citys（岗位城市）: Montreal, Quebec, Canada
Do you want to push the limits of the best Augmented Reality platform in the world? Apple’s Technology Development Group (TDG) delivers algorithms that drive revolutionary Apple products, including the augmented reality (AR) platform ARKit to create ground-breaking new products.
We are looking for a versatile computer vision engineer who is passionate about developing vision-based solutions in service of making human interaction with computers more natural.
You will have the opportunity to be part of our extraordinary team of computer vision and machine learning software engineers to discover and build solutions to previously-unsolved challenges and push the state of the art in AR algorithms that will change the way people experience the world!
To succeed within this role, you should have shown experience in several of the following areas:
Expert knowledge in machine learning and deep learning principles
Strong fundamentals in computer vision
Experience with one or more deep learning libraries (e.g., Tensorflow, PyTorch, Keras)
Track record of successful projects in video analysis (e.g., classification, object tracking, activity recognition)
Proficiency in Python development adhering to best coding practices
Experience developing in C/C+is preferred
The successful candidate embraces working in a dynamic environment in more ways than one. In this role, you will be in a highly collaborative, cross-functional group pushing the boundaries to develop the most capable algorithmic solutions. You will have ample opportunity to think broadly while considering tradeoffs during the research phases and to be deeply focused when meeting the performance targets. As is the work environment, the challenge at hand is dynamic and experience with computer vision systems that require temporal perception and reasoning will be prioritized.
Your responsibilities will also include:
-Development of state-of-the-art algorithms for video analysis
-Design of novel data generation/training methodologies
-Advising on feature definitions/promising development directions in cross-functional groups