
Develop computer vision and deep learning algorithms for visual inspection (defect detection, classification, quality validation) and vision-based navigation (localization, visual servoing, pose estimation)
Design data capture strategies, apply augmentation techniques, and train/fine-tune models for inspection and navigation tasks
Build and maintain data pipelines and MLOps workflows for training, evaluation, model versioning, and production monitoring
Collaborate with Mechanical engineers to design illumination setups and optimize imaging configurations
Support model inference optimization for GPU deployment using CUDA, TensorRT, and related frameworks
Harden perception solutions for production reliability and work with field teams on deployment and customer rollouts
BS or MS in Computer Science, Electrical Engineering, Optics, or a related field with 1–3 years in computer vision/ML
Strong Python skills with experience in PyTorch or similar frameworks
Familiarity with image acquisition, camera systems, and sensor integration
Solid understanding of imaging systems (cameras, sensors, optics, lighting)
Familiarity with 3D geometry, pose estimation, and basic electronics for vision systems
Experience with GPU inference optimization and industrial camera standards (e.g., GigE Vision, GenICam)
Familiarity with camera sensor characteristics (rolling vs global shutter, dynamic range, noise)
Exposure to C/C++, MLOps tools, or data annotation workflows
Experience with data annotation, labeling workflows, and active learning strategies
Familiarity with robotics/vision topics (SLAM, ROS2, sensor fusion) and manufacturing/quality systems
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Between 200 - 500 employees
2018
$437,000,000
Series C
$106,000,000 USD
Debt Financing
$20,000,000 USD
Series C
$106,000,000 USD
Debt Financing
$20,000,000 USD
Debt Financing
$32,000,000 USD
Debt Financing
$32,000,000 USD
Series B
$100,000,000 USD
Series B
$100,000,000 USD
Series A
$179,000,000 USD
Series A
$179,000,000 USD