Sr. ML Architect

Technical Expertise

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods
• Expert knowledge in Python with strong proficiency in SQL and ML frameworks (scikit-learn, TensorFlow, PyTorch)
• Should have done one or more projects involving fine-tuning with LLMs
• Experience in feature selection, building and optimising classifiers
• Experience working with backend technologies such as Flask/Gunicorn etc.
• Extensive experience with deep learning architectures (CNNs, RNNs, Transformers, GANs) and modern optimization techniques
• Hands-on experience with generative AI technologies including LLMs (GPT, BERT, T5), prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and  MCP integration for context-aware AI applications.
• Experience designing and implementing AI agent architectures, multi-agent systems, and autonomous decision-making frameworks
• Strong expertise in document processing, OCR, information extraction, and computer vision applications for automated validation systems
• Experience with conversational AI, voice recognition technologies, and building intelligent chatbot systems
• Proficiency with cloud platforms (AWS, GCP, Azure) and ML operations tools (MLflow, Kubeflow, Docker, Kubernetes)
• Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques
• Proven track record of deploying ML models in production environments with demonstrated business impact
• Experience with A/B testing, causal inference, and experimental design methodologies
• Knowledge of workflow automation, system integration, and API development for seamless AI solution deployment