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We are a series-A startup building perception systems for autonomy. We are based in the San Francisco Bay Area, funded by NEA, and our core team includes faculty entrepreneurs (Stanford and UC Santa Barbara) and industry veterans (Uber, Apple, Amazon Lab126, Rohde & Schwarz), who have successfully shepherded signal processing and machine learning innovations to large-scale software for location improvement and safety at Uber, led the development of state-of-the-art computer vision technologies that shipped over millions of Amazon devices, and delivered zero-to-one product experiences at Uber and Box. Our core product grew out of 5+ years of university R&D by our co-founders. You can find out more about us by visiting our website. Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. Our team is building and deploying edge software and cloud services for real-time customer facing products as well as internal big data tools. We look for people with a depth of expertise and experience in one of these areas, and with the intellectual curiosity for interacting with, learning from, and teaching world-class experts in areas outside their expertise. We currently have internship opportunities in the area of perception and tracking. The candidate will join a multi-disciplinary team of scientists and engineers and support multiple teams across the company. Responsibilities Research, design, develop and evaluate advanced state estimation and sensor fusion algorithms for a real-time object tracking pipeline including but not limited to multi-object tracking, object detection and classification, segmentation, and sensor fusion.Work closely with a proactive, highly motivated engineering team to bring future generation object tracking and sensor fusion solutions to Plato products.Develop state of the art object tracking and sensor fusion algorithms for multiple sensors; Tasks include developing, evaluating, benchmarking and deployment into real-time pipelines.Maintain and improve our existing in-house algorithms and models, including continuous evaluation, gap analysis, re-training and fine tuning.Develop evaluation scripts to process large data and accurately measure algorithmic and end to end performance.Present and demo research topics to Plato internal groups. Basic Qualifications Working towards MS or PhD in CS or EE.Strong Python or C++ programming, familiarity with software development best practices, debugging/profiling.Understanding of statistical signal processing and estimation theory.Experience with motion state estimation.Experience with multiple object tracking.Self motivated.Excellent problem solving skills.Excellent communication skills. Preferred Qualifications Senior Ph.D. student.Experience in application and theory of Bayesian inference, Kalman filters, variational Bayes, distributed estimation, sensor fusion including camera and radar.Experience with heterogeneous sensor fusion. Publications in major conferences and journals. Statistical modeling, analysis, and significance testing.
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