MS or PhD in Computer Science, Electrical Engineering, or related field, or equivalent experience.
5+ years of experience in computer vision and/or machine learning.
Strong programming skills in Python.
Deep expertise with PyTorch for model development.
Experience optimizing ML models for GPU inference in production environments.
Proven ability to transition ML/CV models from prototype to production.
Experience with image acquisition and camera systems.
Responsibilities
Develop and optimize visual inspection algorithms for defect detection and classification.
Optimize model inference for GPU deployment using CUDA and TensorRT.
Collaborate with mechanical engineers to enhance inspection setups.
Maintain data pipelines for model training and evaluation.
Partner with the platform team to implement MLOps practices.
Ensure production reliability through robust inspection solutions.
Support deployment of inspection solutions and customer rollouts.
Benefits
Innovative work environment pushing manufacturing technology forward.
Opportunity to contribute to the transformation of the manufacturing industry.
Collaboration with cross-functional teams including engineers and operational staff.
Potential for professional growth with cutting-edge technologies.
Participation in the development of impactful AI and robotics solutions.
Full Job Description
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
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
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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.
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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
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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)
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C/C++ experience for performance-critical components
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Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar)
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Experience with data annotation, labeling workflows, and active learning strategies
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Experience with ROS2
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Understanding of manufacturing processes and quality control methodologies
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Publications or patents in computer vision, deep learning, or related fields
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About Bright Machines
Bright Machines is a technology company that provides software-defined manufacturing solutions. The company was founded in 2018 by Amar Hanspal and is headquartered in San Francisco, California. Bright Machines' platform uses artificial intelligence and machine learning to automate the assembly and testing of products, with the goal of making manufacturing more efficient and cost-effective. The company has raised over $180 million in funding and has partnerships with companies like Jabil and Flex.
