Job Description: AI/ML/GenAI Engineer

Role Summary

We are looking for an AI/ML/GenAI Engineer with 3-5 years of hands-on experience in building AI/ML and Generative AI solutions. The candidate should have practical experience with Python, Machine Learning, LLMs, RAG pipelines, AI agents, vector databases, backend APIs, MLOps and cloud deployment.

Responsibilities:

• Develop AI/ML and GenAI applications such as chatbots, copilots, document Q&A systems, recommendation engines, and AI assistants.
• Build RAG pipelines using embeddings, vector databases, semantic search, metadata filtering, and re-ranking.
• Integrate LLM APIs such as OpenAI, Claude, Gemini, Llama, Mistral, or other open-source/foundation models.
• Design prompt workflows, structured outputs, function/tool calling, and basic guardrails.
• Build AI agents for workflow automation, API calling, data retrieval, and task execution.
• Train, evaluate, and optimize ML/DL models for classification, prediction, NLP, recommendation, or analytics use cases.
• Develop backend APIs using FastAPI, Django, Flask, or similar frameworks.
• Work with SQL/NoSQL databases and process structured/unstructured data.
• Deploy AI services using Docker, Git, CI/CD, and cloud platforms.
• Monitor AI system performance, response quality, latency, cost, and reliability.

Required Skills:

• Strong hands-on experience with Python
• Good understanding of Machine Learning, Deep Learning, NLP, and Generative AI
• Experience with LLM APIs, prompt engineering, structured outputs, and tool/function calling
• Practical knowledge of RAG, embeddings, vector databases, and semantic search
• Experience with AI agents or workflow automation
• Backend development experience using FastAPI, Django, Flask, or similar
• Knowledge of SQL/NoSQL databases
• Experience with Git, Docker, APIs, and cloud deployment
• Ability to debug, evaluate, and optimize AI/ML solutions

Preferred Skills:

• LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, OpenAI Agents SDK
• PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers
• Pinecone, Weaviate, Qdrant, Milvus, FAISS, ChromaDB, pgvector
• Fine-tuning using LoRA/QLoRA/PEFT
• MLflow, LangSmith, Ragas, DeepEval, Weights & Biases
• AWS, Azure, GCP, SageMaker, Bedrock, Kubernetes
• Computer Vision, Speech AI, Multimodal AI, Recommendation Systems

Qualification:

• Bachelors or Masters degree in Computer Science, AI/ML, Data Science, Engineering, Mathematics, or equivalent practical experience.

Good to Have Project Experience:

• AI chatbot or virtual assistant
• RAG-based document Q&A system
• AI agent or automation workflow
• Recommendation system
• NLP/Computer Vision model
• ML model deployed in production
• LLM-based application integrated with backend or web/mobile app