Description

• Master’s degree or PhD in computer science, machine learning, computer vision, engineering, mathematics, statistics, applied sciences, or a related quantitative field, or equivalent experience
• Six or more years of experience in computer vision, machine learning, or related analytical product development, with strong emphasis on deep learning–based vision systems
• Proven ability to rapidly evaluate and down-select between competing modeling approaches using fair comparisons and evidence-based conclusions
• Strong knowledge of modern computer vision techniques, including object detection, classification, and at least one relevant area, such as anomaly detection, few-shot learning, or vision foundation models
• Solid understanding of evaluation methods for rare-event and class-imbalanced problems
• Advanced programming skills in Python and PyTorch or similar frameworks, with experience working in version-controlled development environments
• Demonstrated ability to produce reusable, well-documented code and frameworks for other data scientists
• Strong analytical, problem-solving, communication, and documentation skills, with the ability to engage effectively across technical and business audiences

Desired Qualifications

• Experience with anomaly detection in industrial, infrastructure, or visual inspection contexts
• Familiarity with vision foundation models for transfer learning, embedding-based retrieval, or low-supervision settings
• Experience working with large-scale image datasets and cloud-based machine learning platforms such as AWS, Azure, GCP, or similar
• Background in infrastructure, industrial inspection, manufacturing quality assurance, or other environments where image-based analytics drive operational decisions

Key Skills

Education

Master's degree