Senior Robot Perception Engineer - Visual Inspection/MLOps

RETHINK MANUFACTURING     The only way to ignite change is to build the best team. At Bright Machines, we’re innovators and experts in our craft who have joined together to manufacture the AI and data center infrastructure at the edge. We believe unifying software, intelligent automation, and data is the answer to delivering quality and flexibility at scale. We deliver products to meet the demands of today while continuously investing in our Bright Factory model to take advantage of what comes next. Working with us means you’ll have the opportunity to make lasting, impactful changes for our company and our customers. If you’re ready to apply your exceptional skills to a brighter way of manufacturing AI infrastructure, we’d love to speak with you. BE EMPOWERED TO CHANGE AN INDUSTRY  Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure production. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers, neoclouds, and leading Original Equipment Manufacturers (OEMs) to reduce their time to revenue. With its Bright Factory model, Bright Machines builds higher quality data center infrastructure at scale, addresses increasing market demands for computing power due to the surge of AI, and answers the call to the U.S. national mandate to reshore manufacturing. Bright Machines is headquartered in the San Francisco Bay Area, California, and has an integration center in Guadalajara, Mexico. The company has been recognized as one of Forbes’ AI 50, awarded “Best AI-based Solution for Manufacturing” by AI Breakthrough, named a “Technology Pioneer” by the World Economic Forum, and highlighted by several other leading technology and innovation organizations.

WHAT YOU WILL BE DOING

Develop and optimize visual inspection algorithms for defect detection, anomaly detection, classification, and quality validation using deep learning

Optimize model inference for GPU deployment, leveraging CUDA, TensorRT, and related acceleration frameworks

Collaborate with Mechanical engineers to design illumination setups that maximize inspection accuracy and robustness

Build and maintain data pipelines for model training, evaluation, and continuous improvement

Partner with platform team to establish MLOps practices for model versioning, experiment tracking, automated retraining, and production model monitoring

Harden inspection solutions for production reliability, including monitoring, alerting, and graceful degradation

Work with service engineering and field teams to deploy inspection solutions and support customer rollouts

Define metrics and benchmarks to measure inspection accuracy, throughput, and reliability

WHAT YOU WILL BRING

MS or PhD in Computer Science, Electrical Engineering, or a related field, or the equivalent in experience with evidence of exceptional ability.

5+ years of relevant experience in computer vision and/or machine learning

Strong programming skills in Python

Deep experience with PyTorch for model development and training

Experience optimizing ML models for GPU inference in production environments

Track record of shipping ML/CV models from prototype to production

Experience with image acquisition, camera systems, and sensor integration

IT WOULD BE GREAT IF YOU HAD

Knowledge of lighting and optics for machine vision (diffuse/directional illumination, lens and filters)

Experience with industrial camera systems and standards (GigE Vision, GenICam, CoaXPress)
C/C++ experience for performance-critical components

Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar)

Experience with data annotation, labeling workflows, and active learning strategies

Experience with ROS2

Understanding of manufacturing processes and quality control methodologies

Publications or patents in computer vision, deep learning, or related fields