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Tier-1 brand, metro location, and mid/senior-level role increase applicant competition.
Industrial computer-vision research focus and energy-equipment domain knowledge demand reduce cross-industry transferability.
Explicit PhD/Master experience thresholds, domain expertise, and research/publication requirements make filters stringent.
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Lead development and implementation of AIML and computer vision algorithms for visual inspection, anomaly detection, prognostics, and diagnostics in energy equipment.
Analyze large datasets to identify patterns and optimize AIML models including CNNs and generative models for scalable, high-performance solutions.
Collaborate cross-functionally to integrate AIML solutions into systems and demonstrate real-world impact via prototypes and intellectual property contributions.
PhD with 5+ years relevant experience OR Masters with 7+ years relevant experience in AI/ML or related field from reputed institution.
Strong expertise in machine learning, computer vision (image processing, object detection, segmentation), and deep learning architectures (CNNs, Vision Transformers).
Proficiency in Python, TensorFlow, PyTorch, OpenCV, and experience with data analysis tools like pandas, NumPy, plus software development best practices including version control and agile.
Relocation assistance is provided; Work Experience Required: Explicitly specified as above.
Experienced researcher with strong practical application skills in industrial visual inspection and image-based diagnostics for energy sector challenges.
Capable of designing scalable machine learning models and conducting experiments to validate AIML solutions' efficacy and reliability.
Ability to lead research initiatives and support cross-functional integration to deliver prototypes, document findings, and contribute to patents and scientific publications.