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Company Overview
A technology company is developing an AI-powered operating system for physical retail. Its autonomous robots and multimodal computer vision platform transform complex and constantly changing retail stores into accurate, actionable intelligence for leading retailers worldwide.
Key Responsibilities
Design, train, validate, and deploy production computer vision models for object detection, segmentation, OCR, barcode localization, product recognition, shelf understanding, and other customer-facing computer vision applications.
Curate, clean, version, and analyze large real-world training datasets.
Perform hard negative mining, annotation quality assurance, data audits, and active learning workflows.
Research and implement improvements to model architectures, loss functions, data augmentation, synthetic data generation, and evaluation methodologies.
Improve model precision, recall, latency, robustness, and performance across different customer environments.
Contribute to model validation, release gates, inference wrappers, ONNX/TensorRT exports, and production monitoring.
Help ensure computer vision models remain reliable and effective in real-world customer environments.
Build internal tools for model evaluation, annotation review, error mining, data visualization, dataset exports, and deployment readiness.
Collaborate with Product, Customer Success, Data, Robotics Software, and Field Operations teams to translate customer issues into model and pipeline improvements.
Monitor developments in open-vocabulary detection, promptable segmentation, multimodal product understanding, visual search, OCR, and edge inference.
Evaluate emerging computer vision and AI technologies and identify opportunities to apply them to customer-facing solutions.
Support the complete model lifecycle, including data preparation, annotation quality, training, evaluation, release, monitoring, and production debugging.
Required Qualifications
5+ years of experience in computer vision, applied machine learning, robotics perception, or related production AI systems.
Strong Python programming experience.
Hands-on experience with PyTorch or TensorFlow.
Demonstrated experience training and evaluating object detection, segmentation, OCR, visual search, or image recognition models.
Strong understanding of dataset curation, annotation quality, model evaluation, error analysis, and experimentation.
Experience building maintainable production code and data pipelines in a Linux-based environment.
Experience using AI-assisted coding and automation tools to accelerate software development, debugging, experimentation, and engineering workflows.
Strong judgment and ability to validate, review, and improve AI-generated code and outputs.
Ability to balance research quality with production constraints, including latency, compute, memory, robustness, and deployment requirements.
Strong communication and collaboration skills.
Customer-focused mindset with the ability to connect technical improvements to measurable business value.
Why This Role Is High Impact
Work with dense, cluttered, real-world visual scenes where model accuracy directly contributes to customer value.
Help improve retail use cases such as out-of-stock detection, price accuracy, promotional compliance, top-stock visibility, and product location intelligence.
Contribute across the complete computer vision model lifecycle, from data and annotation through production deployment and monitoring.
Work on challenging computer vision problems involving real-world retail environments and constantly changing visual conditions.
Collaborate across engineering, product, data, robotics, and customer-facing teams to deliver measurable improvements.
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