Applied AI /ML Associate

Are you ready to shape the future of banking with cutting-edge AI solutions? Join our dynamic team to transform client onboarding and document operations, partnering with business leaders to deliver measurable results in a fast-paced, collaborative environment. Job Summary As an AI Practitioner within the client onboarding and documentation organization, you will: • Design and implement AI-driven solutions to streamline onboarding and document-intensive banking operations. • Lead the development and deployment of document intelligence models, LLM-based data extraction frameworks, and automation pipelines to improve efficiency and accuracy. • Serve as an individual contributor, deeply involved in solution design, model development, and deployment. • Potentially transition into a team leadership role as the AI portfolio grows and solutions scale across functions. • Apply advanced AI expertise and banking domain knowledge to deliver impactful, production-grade solutions for onboarding and KYC processes. Job Responsibilities • Deliver production-grade AI solutions for document understanding and onboarding automation. • Build and deploy LLM-powered extraction and summarization frameworks for unstructured documents. • Achieve measurable improvements in accuracy, turnaround time (TAT), and operational efficiency. • Develop reusable AI modules and APIs to enable rapid adoption across operations functions. • Lead and expand a specialized AI team as solution scale and business demand increase. • Design, implement, and optimize AI models and algorithms for diverse business applications. • Collaborate with stakeholders to gather requirements and translate them into effective AI solutions. • Analyze large datasets to extract actionable insights and support data-driven decisions. • Ensure all AI initiatives comply with data privacy, governance, and ethical standards. • Monitor and maintain model performance, retraining as needed to ensure reliability. • Drive innovation by exploring emerging AI frameworks and technologies for continuous improvement. Required Qualifications, Capabilities, and Skills • Atleast4 years of experience in AI/ML, with at least 4 years in NLP, Document AI, or Generative AI. • Strong foundation in machine learning and deep learning algorithms (classification, clustering, entity extraction, semantic similarity). • Hands-on experience with TensorFlow or PyTorch, scikit-learn, HuggingFace Transformers, and spaCy. • Proven expertise in building document intelligence solutions (classification, OCR, key-value extraction, summarization). • Proficiency in Python, SQL, Pandas, and experience with data ingestion and preprocessing pipelines. • Experience deploying AI models to production, including lifecycle management and monitoring. • Skilled in FastAPI or Flask, Docker, CI/CD, and API integration. • Strong experience with LLM-driven workflows, prompt engineering, RAG, and LLM fine-tuning. • Familiarity with OCR tools (Tesseract, Amazon Textract, Azure Form Recognizer, or Google Document AI). • Demonstrated ability to drive AI solution design and deployment independently. • Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field. Preferred Qualifications, Capabilities, and Skills • Experience in banking client onboarding, KYC/AML, and document verification processes. • Familiarity with corporate onboarding documentation and regulatory compliance in BFSI or regulated domains. • Experience with multimodal document models (LayoutLMv3, Donut, DocFormer) and advanced NER/entity linking. • Integration experience with OpenAI, Anthropic, Cohere, or open-source LLMs (LLaMA, Mistral). • Knowledge of data privacy, governance, and AI explainability frameworks in financial services. • Track record of cross-functional collaboration with operations, data engineering, and low-code teams. • Ph.D. or advanced specialization in AI or related field.