Member of Technical Staff, Machine Learning

Pace BPO • New York, NY

2d • Onsite

About The Position

We’re looking for a Machine Learning Engineer who will work broadly across our product's capabilities. You will: 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 Team characteristics The Pace team has a couple of defining characteristics: Integrity: The most important thing is working with good people who want to have a massive impact on the world. Our team genuinely want to do the best work of their careers and know it’ll take 5-10 years of focus to deliver. 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. Trajectory Equally important is that we want to invest in you for the long-term. You’ll be leading the company not just in engineering but across many potential paths: → Engineering leadership → GM of a business line We want to support you to grow at Pace and beyond for the long-term. We’re a <20 person team based in-person in New York. We’re lucky to be perfectly positioned with leading customers and top investors to make a real impact on one of the largest industries in the world.

Requirements

• 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

Nice To Haves

• Experience in the insurance space
• Experience with computer use models

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed