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Medium: strong employer brand, metro location, and mid-level experience, but specialized generative CV skills limit applicant pool.
High: role requires specialized generative-AI and industrial computer-vision research experience and strong academic credentials.
High: explicit top-institute degree requirement, minimum 3 years, and many mandatory ML/CV technical skills.
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Advance Generative AI and deep learning methods for practical computer vision applications including synthetic data generation and industrial image inspection.
Develop, evaluate, and monitor computer vision models across the full AI lifecycle, addressing challenges like limited data, data drift, and model degradation.
Collaborate cross-functionally to prototype and integrate scalable AI solutions for real-world industrial and business use cases.
Ph.D., M.S., or M.Tech in Computer Science, AI, Machine Learning, Electrical/Electronics Engineering, or closely related field from top institutes (e.g., IITs, IISc).
At least 3 years of professional or applied research experience in computer vision, deep learning, Generative AI, or related areas.
Strong hands-on skills in Python and PyTorch with experience in CNNs, transformers, generative models (diffusion, GANs, VAEs), and computer vision tasks like classification, detection, segmentation, or anomaly detection.
Proficiency with tools/libraries such as NumPy, pandas, OpenCV, scikit-learn, Hugging Face ecosystem, and experience in model evaluation metrics and rigorous experimental design.
Experienced researcher-engineer capable of transitioning advanced Generative AI and computer vision research into robust, scalable industry solutions.
Skilled in handling real-world data challenges such as rare events, class imbalance, domain shift, and continuous model monitoring in production environments.
Able to work effectively across interdisciplinary and geographically distributed teams bridging research, engineering, and product domains.