Pace turns operating procedures for carriers, brokers, and MGAs into agentic systems that execute complex workflows across documents, systems, and customer channels. Backed by Sequoia.
About the role
We’re looking for a Machine Learning Engineer who will work broadly across our product's capabilities. Ambition: The ambition for this company is not just a good vertical AI business but a $100bn+ outcome across vertical services. We’re looking for people that raise that level of ambition. Often times this means they want to be the best at what they do, become leaders at scale or one day start their own company. Pace will be the best place to learn, deliver impact and advance your path to do something great.
More about this role
Pace is an AI-native business process outsourcer for insurers. We combine the speed of AI agents with expert review by our insurance operations team to automate insurance tasks. Almost $400bn per year is spent on outsourcing in financial services every year. We’re here to change that working side-by-side with some of the largest companies in the world.
We’re looking for a Machine Learning Engineer who will work broadly across our product's capabilities.
Develop models for insurance-specific tasks beyond the reach of leading models
Experiment with open-source fine-tuning to tackle some of our hardest use cases across computer use, voice, and/or unstructured data extraction
Transform our toughest ML challenges into tractable solutions with clear roadmaps and timelines
3+ years of experience in production-grade AI/ML engineering
Proven track record of working on AI/ML projects from concept to production.
Experience fine-tuning open-source LLMs and deploying them to production
Experience working with multi-modal models
Experience in the insurance space
Experience with computer use models
Integrity: The most important thing is working with good people who want to have a massive impact...
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