Lead Engineer - AI

About the Role We are seeking a Lead Engineer with strong expertise in Computer Vision and working knowledge of Generative AI . This role requires a hands-on leader who can take ownership of delivering end-to-end AI solutions while guiding a team of 8–10 engineers. The right candidate will balance technical depth, solution delivery, and people management . Key Responsibilities: End-to-End AI Delivery: Drive the entire lifecycle of AI solutions – requirement analysis, data preparation, model development, optimization, deployment, and monitoring in production environments. Computer Vision Solutions: Develop models for object detection, recognition, tracking, OCR, and video analytics. Optimize models for real-time performance (GPU/edge devices such as NVIDIA Jetson). Ensure robustness in challenging conditions (e.g., occlusion, lighting, class imbalance). Generative AI Applications: Integrate LLMs and multimodal AI for use cases like video summarization, natural language queries, automated insights, and incident reporting. Build practical workflows combining CV and GenAI (e.g., retrieval-augmented search across video data). Technical Leadership: Provide architectural guidance for AI pipelines (data ingestion → model inference → post-processing → serving). Establish coding standards, review best practices, and mentor junior engineers. Drive MLOps practices (CI/CD, model monitoring, drift detection, retraining strategies). Team Management: Lead and mentor a team of 8–10 engineers, fostering growth and accountability. Collaborate with product managers and stakeholders to translate business problems into measurable AI solutions. Ensure timely delivery with high technical quality. Innovation & Quality: Stay updated with emerging tools in CV and GenAI, evaluate applicability, and introduce best practices. Focus on scalability, cost optimization, and practical deployment challenges. Required Qualifications: -Education: B.E./B.Tech/MCA in Computer Science, IT, or related field. -Experience: 5–10 years in AI/ML with preferably 2 years in a team lead role. -Technical Expertise: Computer Vision: Proficiency in frameworks like PyTorch, TensorFlow, and OpenCV. Experience with object detection (YOLO, Faster R-CNN), segmentation, OCR, or tracking algorithms. Generative AI: Exposure to LLM-based solutions (LangChain, RAG pipelines, or similar frameworks). Ability to integrate GenAI into CV workflows. Deployment & MLOps: Hands-on with APIs (FastAPI/Flask), containerization (Docker), orchestration (Kubernetes), model registries, and monitoring tools. Performance Optimization: Familiarity with GPU acceleration (CUDA, TensorRT, ONNX Runtime) and scaling inference for production workloads. Programming: Strong Python expertise; exposure to C++/CUDA is a plus. -Leadership Skills: Proven record of leading 6–10 member engineering teams. Ability to balance technical depth with delivery…