Job Title

About the Role: We're looking for an AI/ML Tech Lead to drive the design, development, and deployment of machine learning solutions that power our finance intelligence platform. This is a senior hands-on role with a strong focus on technical leadership, architecture, and team mentorship. You will lead initiatives in real-time forecasting, intelligent document processing, fraud detection, and other AI-first features that deliver measurable value to enterprise finance operations. Your work will directly shape how CFOs, finance teams, and auditors interact with data. Key Responsibilities: Lead the end-to-end development of AI/ML features — from problem framing and model architecture to deployment and monitoring Mentor a small team of ML engineers and guide code quality, experimentation processes, and performance optimization Design robust models for: Spend forecasting, budget prediction, expense categorization, fraud/risk detection Architect intelligent document processing workflows (OCR + NLP) for invoices, receipts, and other financial documents Own time-series modeling strategy across the platform using Prophet, ARIMA, LSTM, XGBoost Drive the adoption of Document AI tools (e.g., LayoutLM, Textract, Vision APIs) for structured data extraction from unstructured documents Collaborate with product managers and domain experts to prioritize high-impact AI initiatives Ensure ML models are production-ready and integrated using modern MLOps: Docker, CI/CD, MLflow, scalable APIs Monitor model performance in production: drift detection, retraining pipelines, versioning Required Skills Deep understanding of ML techniques for both structured tabular data and unstructured documents Strong in ARIMA, SARIMA, Prophet XGBoost, LSTM, GRU Classification, regression, clustering for financial applications Proficient in Python and libraries: scikit-learn, NumPy, Pandas, PyTorch, TensorFlow, StatsModels Document AI & Computer Vision Advanced experience with OCR: Tesseract, AWS Textract, Google Vision Worked with LayoutLM, OpenCV, or Document AI tools for layout analysis, key-value, and line-item extraction Experience managing annotated datasets, working with Label Studio, CVAT, etc. Tech Leadership Proven experience leading ML projects, guiding junior engineers, and setting up experimentation workflows Strong track record of integrating ML into production systems using Flask/FastAPI, Docker, Git, and cloud platforms Comfortable making trade-offs between research depth and delivery speed Finance & Data Domain Solid understanding of financial documents — invoices, receipts, GLs, and spend reports Able to work with tabular, image, and PDF-based financial data SQL fluency and familiarity with finance data models or ERP systems