Machine Learning Engineer - Document Digitization (LLMs)-Vice President

Job Responsibilities

• Lead the design, development, and integration of AI-powered document digitization solutions, focusing on extracting information and insights from diverse document types.
• Manage the end-to-end AI/ML lifecycle: model training, validation, deployment, monitoring, and continuous improvement in production environments.
• Employ generative AI, and large language models (LLMs) to automate and optimize document workflows.
• Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.
• Provision and manage cloud resources using infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock).
• Ensure scalability, reliability, security, and compliance of AI/ML solutions, adhering to best practices and governance standards.
• Collaborate with cross-functional teams to reimagine legacy document processing systems using generative AI and LLMs.
• Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
• Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.
• Conduct model validation, human-in-the-loop review, and implement continuous improvement strategies for digitization accuracy.
• Contribute to communities of practice and explore new and emerging technologies.

Required Qualifications, Capabilities, And Skills

• Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience.
• Strong proficiency in Python programming; familiarity with Java and front-end technologies (React.JS, AngularJS).
• Hands-on experience with AI/ML model development, deployment, and MLOps practices in production environments.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning).
• Knowledge of generative AI models (GANs, VAEs, transformers, diffusion models) and LLMs.
• Experience with AWS cloud platforms (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
• Familiarity with NoSQL databases (Mongo Atlas, ElasticSearch, OpenSearch, Neo4J).
• Experience with agentic coding approaches, autonomous code agents, and last sprinting code generation.
• Strong understanding of SDLC, CI/CD, resiliency, and security practices.
• Demonstrated ability to accelerate development using AI technologies.
• Experience deploying and maintaining AI/ML solutions in large-scale, production environments.
• Strong problem-solving, communication, and collaboration skills.

About The Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.