Computer Vision Engineer

We are looking for a skilled Computer Vision&Robotics Engineer to design, develop, and deploy advanced vision-based solutions for real-world applications. You will work at the intersection of AI and robotics, building robust systems that operate reliably in production and real-time environments.Key Responsibilities
Design, develop, and deploy computer vision models for real-world applicationsBuild and optimize deep learning models for tasks such as object detection, segmentation, classification, tracking, and pose estimationDevelop scalable image and video processing pipelines for both training and inferenceDeploy and optimize models for real-time and edge environments, ensuring low latency and high efficiencyIntegrate vision models into production systems, including automated and semi-autonomous platformsCollaborate with cross-functional teams (software, hardware, product) to deliver end-to‑end solutionsEvaluate model performance using real-world data and continuously improve accuracy, robustness, and efficiencyStay up to date with the latest advancements in computer vision, deep learning, and applied AI
Required Qualifications
Bachelor's degree in Computer Science, Artificial Intelligence, or a related field2+ years of hands‑on experience in computer vision and deep learningStrong programming skills in PythonExperience with deep learning frameworks such as PyTorch or TensorFlowSolid understanding of core computer vision concepts (image processing, CNNs, feature extraction, object detection)Experience training and deploying machine learning models in production environmentsFamiliarity with model optimization techniques (e.G., quantization, pruning, ONNX)Experience working with image/video datasets and data pipelinesStrong analytical and problem‑solving skills
Preferred Qualifications
Master's degree in Computer Vision, Machine Learning, or a related fieldExperience with real‑world or industrial AI applicationsExposure to robotics or autonomous systemsFamiliarity with edge deployment or performance‑constrained environmentsExperience with cloud‑based ML infrastructure and MLOps workflows
Nice to Have
Experience with infrastructure robustness testing to ensure system stability and reliabilityHands‑on experience updating and validating software on physical robotic systemsExposure to real‑world field testing and evaluating system performance in live environmentsFamiliarity with end-to‑end system validation, including testing under varying operating conditions
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