Machine Learning Engineer – Document Digitization (LLMs)- Senior Associate

About

As a Machine Learning Engineer – Document Digitization (LLMs)- Senior Associate in our organization, you will design, develop, and deploy secure, scalable, and innovative technology products that transform how documents are processed and managed. You will use advanced AI and machine learning to extract, analyze, and manage information, driving strategic business outcomes. You will collaborate with cross-functional teams, mentor others, and continuously seek opportunities for improvement and innovation.

Job responsibilities

• 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. and strong problem-solving, communication, and collaboration skills.

Preferred qualifications, capabilities, and skills

• Experience in financial services, especially investment banking or credit risk operations
• Expertise in agentic AI frameworks, prompt optimization, and fine-tuning SLMs
• Familiarity with distributed computing, data sharing, and DDP training
• Experience in design/code reviews and mentoring teams
• AWS Generative AI Developer Professional certification or equivalent