Senior Staff Research Engineer Netradyne

10.0 - 14.0 years

0 Lacs

karnataka

On-site

As a technology company founded in 2015, Netradyne specializes in leveraging expertise in Artificial Intelligence, Deep Learning, and Edge Computing to provide innovative solutions to the transportation industry. Our technology is utilized in a wide range of vehicles, from passenger cars to semi-trailers, operating on various types of roads. Netradyne is currently seeking skilled engineers to join our Analytics team, which includes graduates from prestigious institutions such as IITs, IISC, Stanford, UIUC, and UCSD. As part of this team, you will be involved in developing cutting-edge AI solutions that enable drivers and fleets to identify unsafe driving scenarios in real-time, thereby preventing accidents and minimizing fatalities and injuries. In this role, your responsibilities will include designing, implementing, and commercializing driver monitoring and driver assistance algorithms. You will have the opportunity to work with extensive datasets and deploy new algorithms/models across thousands of vehicles. As a machine learning software engineer, you may be tasked with developing algorithms to characterize driving behavior, tracking key metrics, architecting data-driven solutions, enhancing machine learning infrastructure, and creating proof of concept solutions that demonstrate novel capabilities. To be successful in this position, you should possess a B Tech, M. Tech, or PhD in computer science, electrical engineering, or a related field. Strong programming skills in Python (required) and C++ (desired) are essential, along with 10+ years of research or industry experience in computer vision and machine learning. You should also demonstrate the ability to translate abstract product concepts into tangible solutions, innovate on challenging problems, and have hands-on experience with edge deployments targeting various hardware platforms. Desired skills for this role include expertise in handling image, video, and time-series data, proficiency in camera calibration, multi-view geometry, 3D reconstruction, and SLAM, as well as experience with state-of-the-art multi-camera BEV and Occupancy prediction algorithms. Additionally, familiarity with road scene understanding, machine learning application in real-world scenarios, and successful statistical experiment conduction would be advantageous.,

Posted 2 days ago

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