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Tier-1 brand and metro location increase applicants, but specialized ML research skills narrow qualified candidates.
Deep ML/CV research and industrial inspection domain expertise limit cross-industry transferability, increasing sensitivity.
Requires advanced degree, explicit years of experience, and specialized ML/CV research expertise, making filters strict.
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Lead and develop advanced AIML and computer vision algorithms for visual inspection, anomaly detection, prognostics, and diagnostics of energy equipment.
Analyze large datasets to extract insights and improve AI-based industrial applications such as image-based defect detection and object recognition.
Collaborate with cross-functional teams to integrate AI solutions into platforms and demonstrate impact through prototypes and scalable implementations.
PhD with 5+ years or Masters with 7+ years relevant experience in AI/ML, computer vision, or related fields from a reputed institution.
Strong expertise in AIML, computer vision, deep learning architectures (CNNs, Vision Transformers), image processing, object detection, and segmentation.
Proficiency in Python and frameworks like TensorFlow, PyTorch, OpenCV; experience with tools like pandas, NumPy, and version control (Git).
Relocation assistance provided; Work Experience Required: Explicitly stated (PhD+5yrs or Masters+7yrs).
Experienced in applying advanced AIML and computer vision techniques to industrial/energy sector visual inspection and diagnostics problems.
Capable of independently designing experiments, building prototypes, and contributing to intellectual property and scientific publications.
Comfortable working in a research-driven, collaborative environment involving cross-disciplinary teams and product integration.