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.