Enable robots to operate safely around people by developing robotic perception technologies
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.
Responsibilities
- 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.
Other
- 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.
- Eligible to work in the United States
- We are not able to sponsor visas for this position
