Gen AI Lead
22 hours ago
Job Description:
Role Overview:
We are seeking a passionate and hands-on Gen AI Lead who is deeply experienced in the latest
developments in Generative AI (including LLMs, RAG, LoRA, QLoRA, etc.), with a strong foundation
in Computer Vision, Image Processing, and Video Analytics. This individual will play a pivotal role in
designing, architecting, and deploying full-stack AI solutions while leading and mentoring a team of
junior and mid-level AI/ML engineers.
Key Responsibilities:
• Lead the end-to-end architecture and execution of Gen AI and Agentic AI projects across
diverse industry domains.
• Research, fine-tune, and deploy Large Language Models (LLMs) using techniques
like RAG, LoRA, QLoRA, and other optimization strategies.
• Design and implement Visual AI and Computer Vision solutions including video analytics,
object detection, segmentation, and real-time processing.
• Build scalable, production-ready AI pipelines, including data ingestion, training, validation,
testing, monitoring, and deployment (MLOps / AIOps).
• Architect multi-modal systems combining NLP, vision, and structured data.
• Evaluate and integrate cutting-edge Gen AI tools, open-source frameworks, and foundation
models.
• Collaborate with business stakeholders and translate functional requirements into scalable
technical solutions.
• Mentor and manage a team of AI/ML engineers; provide architectural guidance, code
reviews, and skill development.
• Ensure model explainability, ethical AI practices, and performance benchmarking.
• Own delivery timelines, documentation, and innovation roadmaps for AI initiatives.
Required Skills & Experience:
• Minimum 7 years of hands-on experience in AI/ML, with at least 3+ years in Generative
AI and LLMs.
• Deep understanding and hands-on experience with:
o LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini)
o RAG pipelines, vector databases (e.g., FAISS, Pinecone, Weaviate)
o LoRA, QLoRA, model fine-tuning and distillation
o Agentic AI frameworks (LangChain, AutoGPT, CrewAI, etc.)
• Proficiency in Computer Vision: OpenCV, YOLO, Detectron2, DeepStream, MediaPipe, etc.
• Experience with video processing pipelines, real-time streaming analytics, and model
optimization.
• Strong background in AI deployment: Docker, Kubernetes, MLflow, FastAPI, CI/CD for AI.
• Familiarity with MLOps / AIOps best practices, performance monitoring, logging, and version
control.
• Expertise in Python, PyTorch/TensorFlow, Hugging Face Transformers.
• Experience with cloud platforms (AWS/GCP/Azure) and GPU environments.
• Strong leadership and communication skills – capable of translating complex concepts into
team action.
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