Posted Jul 13, 2026

Data Scientist – Computer Vision (End-to-End Delivery & Technical Ownership)

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Job Title: Senior Data Scientist Computer Vision (End-to-End Delivery & Technical Ownership) Industry: Power Utilities Location: Remote (Candidates must reside in the San Francisco, CA area) Duration: 6 12 Months Contract Rate: $70/hr. (All-Inclusive) Visa: USC and GC Candidates must have active LinkedIn with Picture and need 2 manager refrences. Required Qualifications • PhD in Computer Science, Machine Learning, Data Science, Statistics, Engineering, Mathematics, or a related quantitative discipline, or equivalent practical experience. • Seven or more years of hands-on experience developing and delivering production-grade Computer Vision and Machine Learning solutions. • Demonstrated experience owning end-to-end projects from business problem definition through deployment, production support, stakeholder adoption, and measurable business outcomes. • Strong expertise in Computer Vision, including object detection, image classification, anomaly detection, segmentation, and modern deep learning methodologies. • Advanced Python skills with experience using PyTorch, TensorFlow, or similar frameworks. Experience working with large-scale image datasets, cloud-based ML environments, MLOps practices, model deployment, monitoring, and lifecycle management. • Strong understanding of model validation, experimentation, performance evaluation, and error analysis methodologies used in production environments. Preferred Qualifications • Experience within utilities, infrastructure inspection, industrial operations, manufacturing, asset management, or related industries where image-based analytics support operational decision-making. • Experience with vision foundation models, few-shot learning, transfer learning, and low-supervision techniques. Previous experience developing anomaly detection solutions in real-world inspection environments is highly desirable. • Prior experience establishing reusable Computer Vision frameworks, standards, governance processes, and delivery methodologies across multiple projects is a plus.