As a Principal 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 functional safety and robot behavior, ultimately creating novel solutions to one of the most important problems in robotics. If you are creative, thrive in a small team environment, and passionate about a world where humans and robots truly work together - come join us!
How you will make an impact:
- Help build the systems that allow our robots to operate safely around people.
- 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.
- Develop data sets, metrics, and validation plans for ML models.
- 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.
We are looking for:
- 7+ years of experience applying ML to robotic 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.
We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas for this position.
#J-18808-Ljbffr
