Bedrock Robotics
Perception Sensor Software Engineer
About this role
Bedrock is seeking a Senior Perception Sensor Software Engineer to build and validate sensor systems for autonomous construction machinery. You'll own the sensor validation framework, develop anomaly detection models, and ensure camera, lidar, and IMU data quality for safety-critical autonomous systems.
What you'll do
- Own sensor validation framework for safety-critical autonomous construction systems
- Develop ML models and anomaly detection approaches for multi-sensor data validation
- Build data pipelines, ground-truth infrastructure, and evaluation frameworks for sensor quality
- Partner with perception and behavior teams to ensure data trustworthiness
- Detect system performance degradation and quantify impact on safe operation
- Characterize sensor data representations and corner cases
What they're looking for
- Deep learning production deployment (PyTorch or similar)
- Python and systems languages (C++, Rust)
- Raw sensor data processing (camera, lidar, IMU)
- 3D geometry and sensor calibration
- Statistical data analysis and anomaly detection
- Coordinate transforms and image re-projection
- Embedded/robotic systems experience
- Sensor physics and failure mode understanding
Benefits
- Work on safety-critical autonomous systems with real-world impact
- Collaborate with industry veterans from Waymo, Segment, and Uber Freight
- Test and deploy cutting-edge technology on heavy construction machinery
- 3-4 days onsite at Bay Area testing facility and SF office
- Part of well-funded ($350M) growth-stage company
- Flexible work arrangements for qualified candidates
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Bedrock Robotics
Bedrock Robotics develops autonomous construction machinery powered by AI and robotics technology. The company is hiring for roles spanning developer infrastructure, simulation systems, hardware engineering, field robotics application, and frontend engineering to support the development and deployment of autonomous excavators and heavy equipment.
View all jobs at Bedrock RoboticsLikely interview questions
- Walk us through a production deep learning model you shipped on an embedded or robotic platform. What were the biggest challenges in getting it to work reliably in the real world?
- Describe your experience with raw sensor data (camera, lidar, IMU). How have you validated data quality and detected when sensor performance degrades?