AI/ML Engineer

Key Responsibilities Design, develop, and deploy AI/ML solutions using Python and modern ML frameworks. Build and optimize Generative AI applications leveraging LLMs such as GPT, Claude, and Llama. Develop and maintain RAG-based systems using vector databases such as Pinecone, Weaviate, or ChromaDB.

Implement NLP pipelines for document intelligence, entity extraction, text classification, semantic search, and conversational AI. Fine-tune, evaluate, and monitor machine learning and deep learning models. Build scalable MLOps pipelines for model deployment, monitoring, versioning, and governance.

Collaborate with data scientists, architects, product owners, and business stakeholders to deliver AI-driven solutions. Implement AI governance, model explainability, bias detection, and compliance controls. Integrate AI solutions with enterprise systems through APIs and microservices.

Required Skills Strong programming skills in Python. Experience with TensorFlow, PyTorch, Hugging Face, LangChain, and LlamaIndex. Hands-on experience with LLMs, Generative AI, Prompt Engineering, and RAG architectures.

Experience with Vector Databases (Pinecone, Weaviate, ChromaDB). Strong understanding of NLP, Deep Learning, Transformers, and Machine Learning algorithms. Experience with AWS SageMaker, Azure ML, or GCP Vertex AI.

Knowledge of Docker, Kubernetes, CI/CD, and MLOps practices. Strong SQL and data engineering fundamentals.