Job Category Data Analytics Business Intelligence BI About Business Adani Group Adani Group is a diversified organisation in India comprising 10 publicly traded companies It has created a world-class logistics and utility infrastructure portfolio that has a pan-India presence Adani Group is headquartered in Ahmedabad in the state of Gujarat India Over the years Adani Group has positioned itself to be the market leader in its logistics and energy businesses focusing on large-scale infrastructure development in India with O M practices benchmarked to global standards With four IG-rated businesses it is the only Infrastructure Investment Grade issuer in India Job Purpose The Lead - Computer Vision AI Labs translates strategic AI initiatives into executional workflows leading a team of AI engineers data scientists and computer vision specialists The Lead oversees the development of AI-powered image analytics model deployment and performance optimization ensuring AI solutions align with business objectives The role also involves collaborating with cross-functional teams to scale AI adoption and enhance real-time decision intelligence across enterprise operations Responsibilities Lead-Computer Vision Scientist-AI Labs AI Model Development Deployment Deliver high-performing AI-driven computer vision models by leading their design training and deployment ensuring accuracy exceeds predefined benchmarks Implement and optimize real-time image processing pipelines utilizing TensorFlow PyTorch and OpenCV to achieve low-latency high-precision performance Enable AI-driven automation and industrial intelligence by successfully integrating computer vision models into robotics manufacturing analytics and process automation systems Improve AI model adaptability and accuracy by establishing automated feedback loops retraining mechanisms and performance optimization frameworks Enhance AI scalability and deployment efficiency by refining inference pipelines for cloud AWS Azure GCP and edge computing platforms reducing processing time Image Analytics AI Optimization Develop and deploy advanced image recognition solutions for object detection OCR and anomaly detection ensuring X increase in recognition accuracy Enhance real-time object classification and decision-making by incorporating LiDAR RGB-D and thermal imaging-based AI models into production workflows Reduce AI model inference time and error rates by refining deep learning architectures for low-latency and high-precision analytics in dynamic environments Expand AI-driven automation in IoT and surveillance ecosystems by embedding optimized vision models into smart monitoring and predictive maintenance systems AI Governance Risk and Compliance Ensure full compliance with AI ethics privacy laws and industry best practices by implementing standardized governance frameworks for AI models Establish and enforce model validation processes to eliminate bias improve interpretability and enhance explainability by X across AI deployments Strengthen AI security and reliability by developing risk mitigation strategies anomaly detection protocols and automated compliance audits for AI models Improve model lifecycle management by conducting quarterly audits and performance evaluations leading to an increase in AI deployment success rates Cross-Functional Collaboration Business Integration Integrate AI-driven computer vision models into enterprise applications by collaborating with data scientists software engineers and business leaders to deliver AI-driven insights Accelerate AI adoption across teams by driving hands-on experimentation model validation and successful deployment of AI use cases in business-critical functions Optimize AI deployment pipelines by working with DevOps teams to automate model release cycles through CI CD integrations reducing deployment time Enhance AI-powered decision intelligence by defining transparent business use cases technical requirements and impact metrics with product managers and stakeholders Team Leadership Capability Building Develop a high-performing AI team by managing mentoring and training AI engineers data scientists and image processing specialists in deep learning advancements Enhance team capabilities by leading structured training programs ensuring X improvement in AI proficiency across key technical domains Drive research and innovation in AI labs leading to the development of X new AI solutions per year enhancing business decision-making Expand AI expertise in the organization by leading hiring workforce planning and talent acquisition strategies to build a best-in-class AI R D team Key Stakeholders - Internal Chief Technology Officer CTO Chief Data Officer CDO AI Data Science Teams Product Engineering Teams Business Units Operations Teams Cybersecurity Compliance Teams Key Stakeholders - External AI Research Institutes Universities Regulatory Authorities GDPR AI Act ISO AI Compliance Industry Partners AI Consortiums Technology Vendors Cloud Providers AWS GCP Azure Qualifications Educational Qualification Master s Ph D in AI Computer Science Machine Learning or Computer Vision Preferred from ISI IISc IIT Top AI Universities MBA or Business Leadership Programs Preferred for Business Strategy Integration Certification Preferred but Not Mandatory AWS GCP Azure AI Machine Learning Certification Deep Learning Specialization Coursera Stanford Andrew Ng s DL Program Computer Vision Nanodegree Udacity MIT AI AI Governance Ethics Certification ISO AI Regulatory Frameworks DevOps for AI MLOps Certification Google Kubernetes TensorFlow Extended - TFX Work Experience Range of years 10 years

📌 Lead - Computer Vision Scientist-ai Labs (Ahmedabad)
🏢 Adani Group
📍 Ahmedabad