Description

You will design and build AI/ML solutions across various domains.

Responsibilities

• Design and implement ML/AI models for regression, classification, NLP, time series, and clustering using large datasets.
• Develop and deploy Generative AI and LLM-based solutions using frameworks like LangChain and RAG.
• Design and develop scalable AI Agents, focusing on performance, cost, and reusability.
• Apply MLOps practices for model versioning, automation, and monitoring.
• Create RESTful APIs and AI microservices using FastAPI/Flask/Django, deploying them on Docker/Kubernetes.

Required Skills

• 5–10 years of experience in Data Science or AI Engineering.
• Proficiency in Python, NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
• Strong knowledge of Generative AI, RAG, embeddings, and prompt engineering.
• Experience building APIs and microservices using FastAPI, Flask, or Django.
• Knowledge of MLOps, CI/CD, Docker, and Kubernetes.
• Familiarity with LLMs, Hugging Face, and deployment via Ollama/LMStudio.
• Experience managing data ingestion from systems like MongoDB, ClickHouse, and data lakes.
• Knowledge of databases including PostgreSQL, MongoDB, and Vector databases like Pinecone or Chroma.

Key Skills

Education

Any Graduate