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.