Description

You will develop and deploy machine learning solutions for the RxQuality MFC project, including computer vision, LLM integration, and MLOps workflows.

This role is hybrid.

Responsibilities

• Build and deploy machine learning solutions for the RxQuality MFC project.
• Train and fine-tune computer vision models for object detection, segmentation, and OCR.
• Develop and serve REST APIs for model inference using FastAPI or similar frameworks.
• Implement MLOps workflows using containerization and CI/CD pipelines.
• Integrate LLM, GenAI, and RAG pipelines into enterprise systems.

Required Skills

• 7+ years of hands-on experience in applied machine learning, deep learning, and AI system deployment.
• Strong Python engineering background.
• Deep learning frameworks including TensorFlow, PyTorch, and Keras.
• Computer vision expertise using OpenCV and models like YOLOv5/v8, EfficientNet, Faster-RCNN, TrOCR, or Vision Transformers (ViT).
• Experience serving inference via TF Serving, TorchServe, or FastAPI.
• MLOps proficiency with DVC, MLflow, Git, CI/CD, Docker, and Kubernetes.
• Cloud deployment experience on Azure, AWS, or GCP.
• LLM/GenAI experience with GPT-4, LLaMA, or Claude, including fine-tuning and prompting.
• Knowledge of RAG pipelines and Agentic AI architectures like LangChain, CrewAI, or AutoGPT.

Preferred Skills

• Foundations in statistics, optimization, AI governance, and model explainability.

Key Skills

Education

Any Graduate