Senior Machine Learning Engineer

What You'll Be Doing

• Design and implement scalable machine learning pipelines, optimizing prompt engineering workflows to enhance accuracy and efficiency in submission intake processes across multiple insurance use cases.
• Evaluate and benchmark open-source large language models (LLMs), selecting and fine-tuning the most effective ones to address business-specific requirements while maintaining an eye on adaptability and future innovation.
• Continuously research and incorporate the latest advancements in prompt engineering and model optimization to refine prompts for precision and relevance, contributing to a robust, cutting-edge ML infrastructure.
• Collaborate cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.

Who We Hope You Are

• Proven experience as a Machine Learning Engineer or similar role (at least 5 years), with a strong focus on pipelining LLM models over the last 3 years.
•  Proven experience in designing, training, benchmarking, and fine-tuning machine learning models, particularly with NLP models and large language models (LLMs) along with familiarity with open-source models is a plus.
• Experience in building scalable ML pipelines using tools such as Kubeflow. Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
• Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
• Great communication skills with the ability to convey complex findings to non-technical audiences.