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As a Senior Staff Perception/ML Research Engineer on the Perception and Safety R&D Team, you will join a small cross-functional group developing robotic perception technologies that will enable our robots to operate safely around people. Every day you will help research, design, and build machine learning-based perception models and algorithms to run on our robots. Your work will enable our robots to understand their environment and recognize humans. You will help integrate your algorithms into embedded systems intended to make our robots safe and reactive. In this role you will chart a path by combining the best of ML with modern safety concepts and robot behavior, ultimately creating novel solutions to one of the most important problems in robotics.
Job Responsibility:
Help build the systems that allow our robots to operate safely around people
Develop datasets, metrics, and validation plans for ML models
Build, validate, and deploy ML models to detect hazards, humans, and other environmental features
Integrate these models onto our robots' embedded systems to collect data and evaluate performance
Work to improve model accuracy and run-time performance of models on specific hardware
Lead cross-functional technical efforts involving interdisciplinary efforts to develop robotic systems
Work closely with a small team to design and prototype new payloads, platforms, and product features which create safety features for our robots
Requirements:
7+ years of experience working with perception sensor data, including stereo, LiDAR, radar, ToF, or IR data
5+ years of experience applying ML to perception problems, ideally on embedded systems
Deep knowledge of state of the art in related areas including human detection, autonomous vehicle and driver assist systems, and robot safety
Experience developing and deploying ML-based perception software for time-sensitive control systems, such as robotics
Experience developing specifications for perception systems from high-level product requirements
Experience with the full lifecycle of deep learning development, including network design, data management, training, evaluation, hyperparameter search, deployment, and validation
Strong communication skills, including ability to author technical documentation and deliver presentations on technical topics
History of leading cross-functional technical efforts through planning, technical requirement development, and interdisciplinary collaboration
History of working in small, interdisciplinary teams