Computer Vision Engineer

Company Description Sigmatic is a technology company focused on the ambulatory surgery center (ASC) environment, automating manual workflows to improve efficiency and accuracy. By delivering real-time operational insights, Sigmatic helps ASC teams make faster, data-driven decisions that reduce costs and improve margins. The company leverages advanced artificial intelligence to drive sustainable growth and operational excellence for its customers. Sigmatic’s solutions are purpose-built for ASCs, enabling optimized profits while supporting high-quality patient care.Role Description The Computer Vision Engineer will design, develop, and deploy computer vision models that support automation and decision-making within Sigmatic’s ASC-focused products. Day-to-day responsibilities include building and training pattern recognition and image-processing pipelines, integrating models into production systems, and collaborating with data scientists, software engineers, and product managers to translate clinical workflows into robust technical solutions. The role involves prototyping new algorithms, optimizing existing models for performance and reliability, and maintaining documentation and testing frameworks. This is a full-time hybrid role based in Karnataka, India, with a mix of on-site collaboration and some work-from-home flexibility.Qualifications Strong foundation in Computer Science and Data Science, including algorithms, data structures, statistics, and machine learning.Hands-on expertise in Computer Vision and Pattern Recognition, such as image classification, object detection, segmentation, and feature extraction.Experience applying computer vision and AI in Robotics or automation contexts, including real-world system integration and sensor data handling.Proficiency in programming languages commonly used in AI (e.g., Python, C++), and frameworks such as OpenCV, TensorFlow, PyTorch, or similar.Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field, or equivalent practical experience.Ability to work in a hybrid environment, communicate clearly with cross-functional teams, and translate domain requirements into technical solutions.Experience with healthcare, medical imaging, or regulated environments is an advantage, as is familiarity with cloud platforms and MLOps practices.