AI & Machine Learning Engineer

About LightSpeed

LightSpeed Build Technologies is revolutionizing the construction industry through AI-powered robotics. Our flagship systems—BRUTE for automated wall panel manufacturing and DEX for on-site collaborative construction—are addressing the global housing crisis by delivering unprecedented speed, precision, and affordability in homebuilding.

Position Overview:

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems that make LightSpeed’s construction robots smarter, faster, and more autonomous. You will develop machine learning models for computer vision, predictive analytics, autonomous decision-making, and process optimization—all deployed in real-time production environments where precision and reliability are critical. This role sits at the intersection of cutting-edge AI research and practical industrial application.

What you'll work on:

Machine Learning Development

• Design, train, and deploy ML models for robotic control, quality prediction, and process optimization

• Develop reinforcement learning and imitation learning systems for robot task planning

• Build predictive maintenance models using sensor data to anticipate equipment failures

• Implement anomaly detection for real-time quality monitoring during automated assembly

• Optimize model inference for edge deployment on GPU-accelerated hardware in production

Computer Vision & Perception

• Develop deep learning pipelines for object detection, segmentation, and pose estimation

• Build real-time vision systems for robotic guidance, workpiece tracking, and dimensional verification

• Implement 3D point cloud processing for construction material recognition

• Design and train models for visual quality inspection using depth cameras and industrial imaging

Data Infrastructure & MLOps

• Build ML data pipelines from sensor acquisition through model training and deployment

• Establish data labeling, versioning, and management workflows for training datasets

• Implement model monitoring, A/B testing, and continuous improvement in production

• Design experiment tracking and reproducibility infrastructure (MLflow, Weights & Biases)

Integration & Deployment

• Integrate ML models with ROS2-based robot control for real-time inference

• Optimize models for NVIDIA Jetson, industrial PCs, and edge computing platforms

• Collaborate with robotics engineers on sensor selection, placement, and calibration

• Support scaling ML systems across multiple production cells and sites

Required Qualifications:

AI/ML Expertise

• 4+ years hands-on ML engineering building and deploying production models

• Deep proficiency with PyTorch or TensorFlow for model development and training

• Strong computer vision experience: object detection, segmentation, depth estimation, or 3D vision

• Understanding of reinforcement learning, imitation learning, or robot learning approaches

• Experience optimizing ML models for edge deployment (TensorRT, ONNX, quantization)

Software Engineering

• Strong Python with experience in C++ for performance-critical components

• Experience with ML infrastructure: data pipelines, experiment tracking, model serving

• Proficiency with Linux, Docker, Git, and CI/CD workflows

• Understanding of real-time system constraints for ML inference in production

Preferred Qualifications:

• MS or PhD in Machine Learning, Computer Science, Robotics, or related field

• Experience with robotics simulation: MuJoCo, IsaacSIM, or similar

• Background in manufacturing, industrial automation, or construction technology

• Experience with ROS/ROS2 integration for ML-powered robotics

• Published research or patents in computer vision, robot learning, or related ML

• Experience with NVIDIA ecosystem: CUDA, cuDNN, TensorRT, Jetson platforms

Why Join LightSpeed:

• Build AI systems that directly control physical robots addressing the housing crisis

• Work on rare real-world ML challenges: real-time inference, embodied AI, industrial perception

• Access to rich proprietary datasets from production robot cells

• Hands-on culture with direct access to robots, sensors, and manufacturing environments

• Competitive compensation including salary, equity, and comprehensive benefits

Employment Relationship