Edge ML Engineer - Perception for Autonomous Construction

Bedrock Robotics Inc; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Bedrock Robotics Inc in San Francisco is seeking a Machine Learning Engineer specializing in perception systems. The successful candidate will have 3+ years of experience in deploying production ML models, particularly in contexts involving Lidar and computer vision. Responsibilities include designing early fusion architectures and building robust perception systems for diverse conditions. Ideal candidates will possess expertise in 3D geometry and deep learning frameworks like PyTorch and TensorFlow. This role offers the opportunity to work on cutting-edge technology that enhances construction processes.

Qualifications

• 3+ years of experience taking deep learning models from research to production using frameworks like PyTorch or TensorFlow.
• Deep understanding of 3D transformations, sensor calibration, and geometric projections.
• Experience with fusion architectures at the feature level.

Responsibilities

• Develop and train models that fuse raw Lidar and Camera data for object detection.
• Build robust perception systems for dynamic environments.
• Optimize models for inference on embedded hardware.

Skills

Production ML Experience

3D Geometry & Calibration

Early Fusion Expertise

SOTA Object Detection experience

Systems Fluency

Data Intuition

Job description

Bedrock Robotics Inc in San Francisco is seeking a Machine Learning Engineer specializing in perception systems. The successful candidate will have 3+ years of experience in deploying production ML models, particularly in contexts involving Lidar and computer vision. Responsibilities include designing early fusion architectures and building robust perception systems for diverse conditions. Ideal candidates will possess expertise in 3D geometry and deep learning frameworks like PyTorch and TensorFlow. This role offers the opportunity to work on cutting-edge technology that enhances construction processes.