Über diese Senior Robot Perception Engineer - Visual Inspection/MLOps Stelle bei Brightmachines
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.
ABOUT THE ROLE
As a senior Robot Perception Engineer on the Smart Robotics team at Bright Machines, you will be a hands-on senior contributor responsible for productizing visual inspection solutions for our automation platform. You will own the full pipeline—from algorithm development to production deployment—turning prototype inspection capabilities into reliable, high-throughput features that operate at scale across our automation lines. In this role, you will develop and optimize computer vision and deep learning models for defect detection, classification, and visual validation. You will collaborate closely with cross-functional teams, including Mechanical Engineering and Manufacturing Operations, to design end-to-end inspection solutions that deliver consistent, accurate results under real-world factory conditions. Additionally, you will have the opportunity to shape the inspection product roadmap and drive the adoption of cutting-edge machine learning techniques in an industrial setting.
WHAT YOU WILL BE DOING
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Develop and optimize visual inspection algorithms for defect detection, anomaly detection, classification, and quality validation using deep learning
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Optimize model inference for GPU deployment, leveraging CUDA, TensorRT, and related acceleration frameworks
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Collaborate with Mechanical engineers to design illumination setups that maximize inspection accuracy and robustness
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Build and maintain data pipelines for model training, evaluation, and continuous improvement
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Partner with platform team to establish MLOps practices for model versioning, experiment tracking, automated retraining, and production model monitoring
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Harden inspection solutions for production reliability, including monitoring, alerting, and graceful degradation
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Work with service engineering and field teams to deploy inspection solutions and support customer rollouts
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Define metrics and benchmarks to measure inspection accuracy, throughput, and reliability
WHAT YOU WILL BRING
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MS or PhD in Computer Science, Electrical Engineering, or a related field, or the equivalent in experience with evidence of exceptional ability.
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5+ years of relevant experience in computer vision and/or machine learning
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Strong programming skills in Python
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Deep experience with PyTorch for model development and training
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Experience optimizing ML models for GPU inference in production environments
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Track record of shipping ML/CV models from prototype to production
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Experience with image acquisition, camera systems, and sensor integration
IT WOULD BE GREAT IF YOU HAD
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
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 San Francisco, California, with 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.
