3 Multiview Geometry Jobs

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. 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 in 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. 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! 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.,

Vimaan is looking to onboard multiple Machine Learning Engineers in Bengaluru, India to drive the development of computer vision and machine learning algorithms to power our cutting-edge wall-to-wall warehouse inventory tracking and verification platform. This is a unique opportunity to exploit a treasure cove of unseen real-world data coming from a multi-camera perception system and develop large-scale computer vision and deep learning models to build a product that creates a disproportionate value for the warehouse industry. The role involves hands-on CV/ML software development and deployment from understanding the product requirements, defining Computer Vision functional specs to designing, developing, and deploying CV/ML models in production at scale. The ideal candidate for the Machine Learning Engineer position should have an MS in computer vision, machine learning, AI, applied mathematics, data science, or related technical fields, or a BS with 3+ years of experience in Computer Vision/Machine Learning. They should possess hands-on experience in developing new learning algorithms for computer vision tasks such as object detection, object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation, adversarial and generative models, as well as representational learning with varying amounts of data. Knowledge of current deep learning literature and the mathematical foundations of machine learning is essential. Experience with popular object detection frameworks such as YOLO, SSD, or Faster R-CNN is considered a plus. The candidate should have the ability to train and debug deep learning systems, gain deep insights into data characteristics, and map those to appropriate model architectures. Experience working with inputs from multiple cameras and input modes is advantageous, as is experience in AI Infrastructure, Machine Learning Accelerators, On-Device Optimization, and training and deploying deep learning models on GPU-accelerated platforms. Strong programming skills with Python and experience with ML/DL frameworks like Tensorflow, Pytorch, etc., are required. Prior experience in deploying machine learning models in production environments, working with cloud platforms (e.g., AWS, Azure, Google Cloud), and familiarity with data pre-processing, augmentation, and visualization tools and libraries are necessary. The ideal candidate should be highly motivated, passionate, possess a strong work ethic, and be able to work effectively in a team or independently under supervision in a matrix management environment. Effective communication skills, problem-solving abilities, attention to detail, and a passion for staying at the forefront of technology advancements in machine learning and computer vision are key attributes. They should be able to work in a fast-paced, high-pressure startup environment, adapt to rapidly changing requirements, and convey complex technical concepts to non-technical stakeholders. The Machine Learning Engineer will be responsible for researching, designing, and developing machine learning algorithms and models for various tasks of detection, recognition, and classification for warehouse inventory management. They will implement and optimize deep learning architectures, explore techniques like transfer learning and data augmentation, guide annotation teams, curate and pre-process annotated datasets, collaborate with MLOps for integrating machine learning models into production systems, and conduct thorough performance analysis and evaluation of models using appropriate metrics and tools. It is essential for the Machine Learning Engineer to stay up-to-date with the latest advancements in machine learning and computer vision research and integrate relevant findings into the solutions developed at Vimaan. ABOUT VIMAAN Headquartered in Silicon Valley, with team members around the world, Vimaan is comprised of computer vision and hardware technologists, as well as warehousing domain experts with a successful history in technology startups. Vimaan's primary mission is to deliver computer vision and machine learning solutions to solve long-standing inventory visibility, accuracy, and quality challenges in the supply chain.,

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.,