Senior Machine learning Engineer

Role overview Provide technical leadership for generative AI and large language model capabilities, from data preparation and experimentation through deployment and production monitoring. The work focuses on building secure, scalable AI services for insurance workflows and collaborating across product, engineering, and business teams to deliver practical customer outcomes.

Responsibilities - Design and evolve end-to-end GenAI solutions, including ingestion, feature pipelines, training, fine-tuning, deployment, and monitoring. - Build robust machine learning and LLM pipelines for applications such as claim summaries, underwriting support, pricing insights, and developer tools. - Apply prompt engineering, retrieval-augmented generation, vector search, and fine-tuning to improve reliability and usefulness. - Establish MLOps practices for delivery, experimentation, evaluation, observability, and responsible AI. - Work with product, security, finance, and go-to-market partners to align capabilities with roadmap, governance, and customer needs. - Review designs and code, mentor engineers and data scientists, and improve performance, reliability, and cost efficiency.

Requirements - Five or more years of machine learning or data science experience, including production ML system delivery. - Strong Python skills and experience building scalable ML or LLM services and pipelines. - Knowledge of model lifecycle practices such as CI/CD, experiment tracking, model registries, monitoring, and drift detection. - Experience with classical and gradient-boosting models, neural networks, transformers, and LLM fine-tuning or inference. - Hands-on familiarity with prompt design, RAG, vector databases, and evaluation of LLM quality, safety, and robustness. - Ability to lead technical work, collaborate across functions, and communicate design decisions effectively.

Nice to have - Experience delivering ML workloads on AWS, including services such as S3, EC2, RDS, or SageMaker. - Background applying AI to insurance or other business workflows.

Benefits and work setup - The listing gives a US base salary range of $162,000–$258,000, dependent on factors including experience, skills, and location. It describes health, dental, and vision coverage, paid time off, and a retirement plan for eligible roles; some positions may also qualify for bonus or incentive awards.