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Specialized AI/CV lead role with moderate mid-level experience requirement increases applicant density.
Requires deep CV and GenAI experience plus production MLOps, so backgrounds must be domain-specific.
Multiple mandatory technical areas (CV, GenAI, MLOps, GPU optimization) and explicit years requirement enforce strict filtering.
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Own end-to-end delivery of AI solutions focusing on computer vision and generative AI applications, including requirement analysis through production monitoring.
Lead and mentor a team of 8–10 engineers, establishing coding standards and guiding architectural decisions for AI pipelines and MLOps practices.
Drive performance optimization, scalability, and integration of computer vision models with generative AI workflows for real-time and practical deployment scenarios.
5–10 years experience in AI/ML with preferably 2 years in a team lead role.
Degree: B.E./B.Tech/MCA in Computer Science, IT, or related field.
Expertise in computer vision frameworks (PyTorch, TensorFlow, OpenCV) and generative AI integration (LLM-based solutions, LangChain, RAG pipelines).
Hands-on experience with deployment technologies including APIs (FastAPI/Flask), containerization (Docker), orchestration (Kubernetes), and GPU acceleration (CUDA, TensorRT).
Experienced engineering leader capable of balancing deep technical contributions with delivery and people management for mid-sized teams.
Strong technical background in computer vision model development and generative AI practical application.
Comfortable leading design and implementation of scalable, production-grade AI systems incorporating MLOps best practices.