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.