Location: New York (Flexibility to work remotely for exceptional candidates)
Employment Type: Internship
We’re on a mission to breathe life into software by giving it action taking abilities. We are leveraging recent advances in generative models, reinforcement learning and symbolic AI, to give software the ability to action complex goals. We envision a world in which software applications become their own autonomous agents, trading information, value and decisions with their users and with each other.
We are building a category defining autonomous agent architecture that’s designed from the ground up for complex, high sensitivity, context dependent enterprise software use cases.
Our team is comprised of industry veterans in applied machine learning research and data platforms, who are former leaders and founders from Meta, Monzo and QuantumBlack, amongst others.
As an AI Engineer Intern, you’ll have the opportunity to build a state of the art experience in building generative model architectures. We’ll support you in owning a challenging end-to-end generative model focused problem. If you have a strong bias to action, thrive on ambiguity and desire to own problems end-to-end, we’d love to hear from you.
Work with researchers to extend our generative model prompting architecture.
Take part in implementing our ground-truth data collection platform that powers the fine-tuning of generative action models.
Extend our reference tools and datasets and integrate them into our automated reasoning systems.
Evidence of exceptional ability.
Real world ML development experience.
Publications in top deep learning venues (ICLR, NeurIPS, ICML, CCVPR).
Plus: Experience with generative model architectures, including Retrieval Augmented Generation, Graph Learning, AI agents and tree-search augmented LLMs.
We offer competitive compensation, on par with internships at FAANG. If you present an internship offer from a top tech company and pass our interviews, we will match their compensation and offer a 20% performance based bonus on top of that.
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