AI ML Engineer

Job Summary

We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy machine learning and generative AI solutions that solve complex business problems. The ideal candidate will have hands-on experience with machine learning algorithms, deep learning, NLP, computer vision, and modern AI frameworks. You will collaborate with Data Scientists, Software Engineers, Product Managers, and DevOps teams to build scalable AI-powered applications and production-ready ML pipelines.

Key Responsibilities

• Design, develop, and deploy enterprise-grade AI applications using Large Language Models (LLMs) and Generative AI technologies.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
• Develop AI-powered applications using frameworks such as LangChain, LlamaIndex, and Hugging Face.
• Integrate OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or other enterprise LLM APIs into production workflows.
• Fine-tune, optimize, and evaluate foundation models for domain-specific use cases.
• Build scalable machine learning models using PyTorch or TensorFlow.
• Develop REST APIs using FastAPI or Flask for AI services and model inference.
• Deploy AI/ML applications on cloud platforms including Azure OpenAI Service, AWS SageMaker, and Google Vertex AI.
• Build containerized AI services using Docker and orchestrate deployments using Kubernetes.
• Implement MLOps best practices including CI/CD, model versioning, monitoring, and automated retraining.
• Collaborate with Product Managers, Data Scientists, Engineers, and enterprise clients to deliver AI-driven business solutions.
• Ensure responsible AI practices, model governance, security, privacy, and regulatory compliance, particularly in Healthcare and Insurance environments.
• Stay current with emerging AI technologies, research, and industry best practices.
  
  

• Strong experience with Generative AI and Large Language Models (LLMs).
• Prompt Engineering and prompt optimization.
• Retrieval-Augmented Generation (RAG).
• Fine-tuning and model optimization.
• Embeddings and vector search.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, ChromaDB, or FAISS.
• Strong proficiency in Python.
• Hands-on experience with PyTorch or TensorFlow.
• Experience with LangChain, LlamaIndex, and Hugging Face Transformers.
• REST API development using FastAPI or Flask.
• Strong understanding of software engineering best practices and scalable architecture.
• Experience with Azure OpenAI Service, AWS SageMaker, or Google Vertex AI.
• MLOps tools such as MLflow, model versioning, and CI/CD for ML workflows.
• Containerization using Docker.
• Orchestration using Kubernetes.
• Model monitoring, performance optimization, and production deployment.
  
  

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, Statistics, or a related field.
• Relevant AI/ML certifications are an added advantage.