Machine Learning Engineer / Data Scientist
San Diego, California, United States
Machine Learning and AI
As a Machine Learning Engineer / Data Scientist within the Ground Truth Systems Team, you will be part of a team building infrastructure and tools for exciting new technologies that will shape our future. We build web services that work at scale to support new products and also enable Machine Learning development workflows. We are looking for a Machine learning (ML) engineer with a broad experience and knowledge in machine/deep learning and computer vision. You will be part of every stage of development from concept to deployment. The Engineer will be working on cutting edge problems in efficient data annotation building ML models that assist humans in reducing labeling efforts without sacrificing quality. The candidate should be proficient in the theoretical fundamentals of the above areas with experience in applying them to solve real-world problems.
- Strong coding skills in Python using scientific libraries like numpy, scipy.
- Experience with one or more deep learning frameworks such as PyTorch, Tensorflow, or Keras is a must.
- Experience with training deep neural networks on large-scale datasets.
- Understanding of data structures, software design principles and algorithms.
- Interest in building machine learning models that assist humans in reducing labeling efforts.
- Deep knowledge of traditional ML concepts such as GMMs, SVMs, trees, and boosting as well as more recent deep learning fundamentals.
- Previous publication experience in conferences such as CVPR, ICCV, NeurIPS, and ICLR will be strongly considered
The Video Computer Vision org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We balance research and product to deliver Apple quality, state-of-the-art experiences, innovating through the full stack, and partnering with HW, SW and ML teams to influence the sensor and silicon roadmap that brings our vision to life. Examples include FaceID, Animoji/Memoji, Scene Understanding, People Understanding and Positional Tracking (VIO/SLAM).
Education & Experience
MS or PHD in CS/CE/EE (or equivalent) with emphasis in machine learning and computer vision