TriEye
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  • Published: March 21, 2022
Category
Job Type
Level of education
Undergraduate
Spoken Language needed
English
Level of Hebrew
Medium
Location of job
Tel Aviv/ Ramat Gan
How many relevant years experience do you require for the role:
More than 3 years

Description

TriEye is the pioneer of the world’s first SWIR sensing technology. Based on nanophotonics research, TriEye’s technology is disrupting the world of vision sensors for the automotive market along with other exciting applications.

We are looking for some exceptional talent to join our Perception Research team as a Lead Perception Algo Researcher, leading the research of the perception algorithms for advanced driver assistance and autonomous vehicle and involved with a variety of deep learning based and classical computer vision aspects.

Your Day to Day:

- Leading the research of applicability of various perception solutions (both deep learning based and classical) to the images acquired in non-visible spectrum (SWIR)
- Investigating the dependency of perception quality on the image parameters (like SNR, different types of noise patterns, artefacts etc.) and proposing solutions to improve the perception quality
- Providing continuous feedback to Product and R&D teams based on the research results
- Defining the concepts for different types of object detection and object distance measurement algorithms and validating these concepts by implementation of the POC algorithms
- Defining and building the infrastructure for the data collection and network re-training for the new type of images, optimization of the re-training strategies to minimise the additional data required
- Working with the perception teams on customer side, learning their needs and issues and proposing solutions
- Technical lead of the Perception research team activities.

Why should you be a TriEyoneer?:

- Timing is everything! You want to be a part of a fast-growing deep-tech company backed by industry leaders, as it enters a significant stage of global growth.
- Competitive compensation plan
- Empowering team with a range of growth opportunities
- Interest: TriEye provides a superior sensing solution to solve the low visibility challenge for the automotive industry at a price point that meets high volume manufacturing requirements. TriEye’s breakthrough and proprietary technology enables cost-effective, high-resolution image data and depth perception in all weather and lighting conditions. TriEye’s patented structure and CMOS manufacturing process enables SWIR technology for a variety of applications across automotive, industrial, biometrics, security, consumer electronics, and medical markets. For automotive specifically, our solution is unique in that it leverages SWIR to provide both HD imaging and depth perception under all conditions (e.g., night/low-light, fog, dust, etc.) at a cost that’s an order of magnitude less than that of a LiDAR. Furthermore, being camera-based, we integrate seamlessly even with existing ADAS and AV systems.

Benefits:

- Free Gym Membership
- Parking
- Holidays and Birthday gifts
- Cibus
- Generous vacation allowance
- Happy hours and team events

General statement:

TriEye is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

Requirements

- Bachelor’s or higher degree in computer science
- At least 5 years of proven experience in image processing algorithms development
- At least 2 years of proven experience DNN based computer vision including training of neural networks
- Hands-on experience in implementation of image processing algorithms and deep learning in Python environment
- Good understanding of image quality aspects
- Creative thinking, ability to find out of the box solutions
- Passion to challenges, high self-learning abilities, and readiness to enter new areas
- Background in electro-optics, a basic understanding of sensors and illuminators physics - advantage
- Fluent English

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