Description

Required:

  • 7+ years of hands-on experience in applied machine learning, deep learning, and AI system deployment
  • Strong Python engineering background with ML/DL frameworks: TensorFlow, PyTorch, Keras, OpenCV
  • Proven experience in Computer Vision tasks, including object detection, segmentation, and OCR
  • Experience training and fine-tuning models such as: YOLOv5/v8, EfficientNet, Faster-RCNN, TrOCR, Vision Transformers (ViT)
  • Practical experience building and serving REST APIs for inference (TF Serving, TorchServe, FastAPI)
  • Hands-on with MLOps tools: DVC, MLflow, Git, CI/CD, containerization (Docker/Kubernetes)
  • Cloud deployment experience (Azure preferred; AWS or GCP acceptable)
  • LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc.
  • Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise systems
  • Understanding of Agentic AI architectures (e.g., LangChain, CrewAI, AutoGPT) for orchestrated task agents or workflow automation
  • Strong foundations in statistics, optimization, and deep learning principles
  • Clear understanding of AI governance, fairness, and model explainability

Key Skills
Education

Any Graduate

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