Machine Learning Engineer

Role Overview We are seeking a highly skilled Senior Machine Learning Engineer to join our Automation and AI team. This is a hands-on, high-impact role focused on building and scaling intelligent systems that solve real business problems using modern AI techniques, including Generative AI, RAG, and agent-based architectures. You will play a key role in shaping AI strategy, mentoring engineers, and delivering production-grade machine learning solutions in a fast-paced, purpose-driven environment. Key Responsibilities • Design and implement scalable machine learning and AI solutions to address business challenges • Build and deploy Generative AI, Retrieval-Augmented Generation (RAG), and agent-based systems • Develop AI-powered tools for internal teams (e.g., Claims, Underwriting, Member Services) such as summarization, document processing, and knowledge retrieval • Translate business requirements into practical, production-ready AI solutions using LLMs and internal data • Establish and enhance MLOps practices for deployment, monitoring, and lifecycle management • Partner with business units to evaluate and implement third-party AI tools and platforms • Collaborate with vendors and platform providers to integrate enterprise AI capabilities • Assess intellectual property and data usage considerations in AI solutions • Provide technical leadership, mentor junior engineers, and promote best practices • Work cross-functionally with IT, operations, and automation teams to align AI initiatives with business goals Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Statistics, or related quantitative field with 7+ years of experience • OR • Master’s degree with 5+ years of experience in machine learning engineering • Proven experience developing and deploying machine learning models in production environments • Hands-on experience with NLP, Large Language Models (LLMs), or Generative AI • Strong programming skills in Python • Experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch • Solid understanding of MLOps, model deployment, and monitoring Preferred Qualifications • Master’s degree in a quantitative discipline • Experience in insurance, financial services, or other regulated industries