Principal AI Engineer (Option for remote)

Overview

Join a recently funded Series A start up that empowers small businesses through cutting-edge machine learning and generative AI technology. Our team of AI scientists, engineers, and innovators is dedicated to exponentially improving financial decision-making for individuals and businesses using advanced AI technology. We are seeking a Principal AI Engineer with strong expertise in Knowledge Representation and Reasoning (KRR) to help us bring our vision to life as we grow.

You will significantly shape the future of a fast-growing startup, within a collaborative and transparent culture where every voice is valued. Flexible remote and hybrid work options available as well as competitive salary and equity, generous time-off for rest and recharge, and a comprehensive benefits package including health, dental, vision, and retirement plans.

What You Will Do

• Design, implement, and deploy KRR systems for applications like chat and dialogue-based interfaces, automatic code generation, document understanding, and question answering.
• Develop systems that allow non-expert users to encode accounting knowledge.
• Provide technical leadership to junior engineers and guide them through complex challenges.
• Drive the development and implementation of core KRR components within the AI platform.

What You Will Need to Succeed

• Extensive experience in developing and applying KRR to business applications, along with a proven track record of delivering AI-driven products.
• At least 3 years of hands-on experience with Deep Learning, along with proficiency in tools such as TensorFlow, PyTorch, or equivalent.
• A PhD in Knowledge Representation and Reasoning or relevant equivalent experience.
• Strong experience in building KRR infrastructure at scale, with expertise in techniques like Datalog and Answer Set Programming.
• A solid background in Natural Language Processing, and familiarity with integrating reasoning and machine learning.
• Experience using Large Language Models (LLMs) in the context of KRR systems.
• Experience with coding in Julia and Python, as well as familiarity with Docker and AWS.