Role Description We’re seeking a highly motivated and technically skilled Senior Machine Learning Engineer to join our Automation and AI team. This role requires strong machine learning and data science expertise, excellent coding practices, and the ability to translate real-world business challenges into impactful AI solutions while operating within the core values and operating principles of the organization. The ideal candidate is a hands-on contributor who thrives in a fast-paced, purpose-driven environment. - Develop and coach individual MLE’s. Effectively balance multiple projects and provide guidance to MLE’s on best practices and aligning with organizational objectives. - Architecting solutions to solve business problems. - Partnering with Business Units to assess and implement vendor AI tools. - Assessment of intellectual property and company assets utilized by partners with their AI tools. - Design and implement intelligent systems using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to enhance operational efficiency and decision-making. - Develop AI agents that assist internal teams (e.g., Claims, Underwriting, Member Services) with tasks like summarization, document processing, and knowledge retrieval. - Partner with strategic vendors and platform providers to explore and integrate enterprise-grade GenAI capabilities into AAA Life’s ecosystem. - Translate business problems into practical AI solutions, leveraging internal data and LLMs to create scalable tools. - Implement and refine MLOps practices to support the deployment and monitoring of AI agents and services. - Collaborate with stakeholders across operations, IT, and automation to align AI initiatives with business goals. - Mentor junior engineers and advocate for best practices in responsible, sustainable AI implementation. Qualifications - Bachelor’s degree in a quantitative discipline (Computer Science, Engineering, Statistics, etc.) or related field and 7+ years of hands-on experience developing and deploying machine learning models in production. - OR Master’s degree in a quantitative discipline (Computer Science, Engineering, Statistics, etc.) or related field and 5+ years of hands-on experience developing and deploying machine learning models in production. - Experience working with NLP and/or large language models (LLMs). Requirements - Excellent communication skills and ability to explain ML results to non-technical audiences. - Strong knowledge of MLOps tools and model monitoring. - Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, or PyTorch. Essential Job Functions While performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel, talk, hear and concentrate. Specific vision abilities required by this job include close vision, distance vision, depth perception, and ability to adjust focus. This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements. Reasonable accommodation will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.

• You will be responsible for end-to-end data science cycles, encompassing designing, training, implementing, evaluating, and monitoring machine learning models. • Design and implement highly scalable tools and algorithms based on state-of-the-art Machine Learning and Deep Learning methodologies. • Work across the ML stack, from researching models, working with large datasets, training, and tuning existing models to creating new models, deploying them at scale, analyzing results, and presenting findings to stakeholders across tech and business domains. • Collaborate with cross-functional teams to ensure proper deployment and integration of ML models for new releases.

• Design, prototype, research, and build AI systems for the Company. • Train, evaluate, and deploy ML models in Natural Language Processing, Information Retrieval, AI Agents, Large Language Models (LLMs), and Multimodal Large Models (MLMs). • Improve the quality of the Company's AI Agents and RAG-as-a-service platform, including features such as agentic behavior, hallucination reduction/correction, and agent orchestration. • Publish technical blogs, research papers, and patents.

• Design, prototype, research, and build AI systems for the Company. • Train, evaluate, and deploy ML models in Natural Language Processing, Information Retrieval, AI Agents, Large Language Models (LLMs), and Multimodal Large Models (MLMs). • Improve the quality of the Company's RAG-as-a-service platform, including areas such as multilinguality, self-supervised learning, agentic behavior, and hallucination reduction. • Publish technical blogs, research papers, and patents.