SightX, a deep-tech startup backed by well-known strategic partners is looking for talented professionals who are drawn to solving research and development challenges and are innovative by heart and mind.
Our goal is to Research, Harness, and Deploy complex deep learning modules over edge devices for extreme computer vision challenges.
SightX Core-team is looking for an experienced computer-vision deep learning researcher to join its fearless R&D team alongside some of the best researchers in the field. The research team is in charge of creating cutting edge deep learning solutions aimed for deployment on a variety of edge devices and autonomous platforms deployed in the wild made to solve real-life challenges under the meaningful mission of lifesaving.
Responsibilities:
- Research, design, develop, and implement state-of-the-art machine learning and deep learning solutions for a wide variety of computer vision challenges, including edge solutions over low-voltage chips.
- Work with a multi-disciplinary team of professional researchers and engineers on analysis of deep learning models, map algorithmic bottleneck, and reduce overall model footprint and inference time.
- Research and implement innovative methodologies for the optimization of neural networks, such as: pruning, quantization, compression, neural architecture search, computation optimization.
- Produce optimized solutions that meet high quality, stability, and performance standards.
Requirements:
- Ph.D. (preferred) or M.Sc. in computer science / electrical engineering / Physics / Applied Mathematics, preferably in the field of deep learning and computer vision.
- At least four years of experience related to the following computer vision tasks: object detection, semantic/Instance segmentation, automatic hyper-parameter optimization, and object tracking.
- Proven experience in one of the popular DL frameworks such as PyTorch or TensorFlow.
- Proficiency in Python.
- Strong self-learning and research capabilities – Analyzing models, research possible optimization methods, and developing creative and innovative optimization schemes.
- Team player with strong communication and collaboration skills.
Advantage:
- Experience in implementation of computer vision and deep learning models for edge devices.
- Experience in low-voltage chipsets.
- Leadership experience.
- Experience in optimization methods of deep learning models for edge devices.
