Description

You will develop and deploy machine learning solutions across the stack.

Responsibilities

• Design and implement AI/ML pipelines, covering data preprocessing, model training, and fine-tuning.
• Engineer and deploy Retrieval Augmented Generation (RAG) pipelines using vector databases and graph knowledge management.
• Develop scalable, reusable systems using Python, focusing on RESTful APIs and async programming.
• Integrate and optimize Generative AI frameworks, including prompt engineering and fine-tuning.
• Maintain and improve the deployment lifecycle using CI/CD and containerization standards.

Required Skills

• 5+ years of professional experience in AI/ML development.
• Expert proficiency in Python, including FastAPI and Flask.
• Hands-on experience with GenAI frameworks: LangChain, LlamaIndex, LangGraph, and Bedrock.
• Proven capability in model development using TensorFlow, PyTorch, and SciKit-learn.
• Experience implementing knowledge management via vector databases and graph structures (Neo4j).
• Strong understanding of cloud deployment practices, specifically AWS, and containerization (Docker/Kubernetes).
• Solid grounding in software quality engineering principles and automation.
• Experience architecting solutions leveraging agent-based architectures or Graph databases.

Key Skills

Education

Any Graduate