Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.
About Netradyne
Founded in 2015, Netradyne is a technology company that leverages expertise in Artificial Intelligence, Deep Learning, and Edge Computing to bring transformational solutions to the transportation industry. Netradyne’s technology is already deployed in thousands of vehicles; and our customers drive everything from passenger cars to semi-trailers on interstates, suburban roads, rural highways—even off-road.
Netradyne is looking for talented engineers to join our Analytics team comprised of graduates from IITs, IISC, Stanford, UIUC, UCSD etc. We build cutting edge AI solutions to enable drivers and fleets realize unsafe driving scenarios in real-time to prevent accidents from happening and reduce fatalities/injuries.
Role and Responsibilities
You will help design, implement and commercialize driver monitoring and driver assistance algorithms. You will have access to very large datasets and will get to deploy new algorithms/models into thousands of vehicles. As a machine learning software engineer, you may
- Design and commercialize algorithms characterizing driving behavior.
- Design, implement and track key metrics; and architect data-driven solutions.
- Improve machine learning infrastructure for scalable training and inference.
- Innovate and develop proof of concept solutions showcasing novel capabilities.
Requirements:
- B Tech, M. Tech or PhD in computer science, electrical engineering or a related area.
- Excellent programming skills – Python(required) and C++ (desired).
- 7+ yrs with Research or industry experience within computer vision and machine learning
- Ability to take abstract product concepts and turn them into reality.
- Ability to innovate on cutting-edge problems without documented solutions.
- Hands-on experience in handling edge deployments targeting various HW platforms.
Desired Skills:
- Experience with image, video and time-series data
- Experience with Camera calibration, multi-view geometry, 3D reconstruction, SLAM
- Experience with SOTA multi-camera BEV and Occupancy prediction algorithms.
- Experience with road scene understanding (objects, lanes, intersections, signs etc.)
- Experience with successfully applying machine learning to solve a real-world problem.
- Experience with conducting successful statistical experiments.
We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.
If there is a match between your experiences/skills and the Company's needs, we will contact you directly.
Netradyne is an equal-opportunity employer.
Applicants only - Recruiting agencies do not contact.
Recruitment Fraud Alert!
There has been an increase in fraud that targets job seekers. Scammers may present themselves to job seekers as Netradyne employees or recruiters. Please be aware that Netradyne does not request sensitive personal data from applicants via text/instant message or any unsecured method; does not promise any advance payment for work equipment set-up and does not use recruitment or job-sourcing agencies that charge candidates an advance fee of any kind. Official communication about your application will only come from emails ending in ‘@netradyne.com’ or ‘@us-greenhouse-mail.io’.
Please review and apply to our available job openings at Netradyne.com/company/careers. For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website.
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