About this role

▸about Maple Finance — company background

Hi 👋 I’m Aidan, founder of Maple.

At Maple, we’re building AI agents that work for restaurants. These agents answer calls, take orders, book appointments, and handle real customer interactions over natural voice.

But our bigger mission goes deeper: we’re building automated ontologies that model how businesses actually operate — their services, workflows, constraints, and language — so our agents can adapt to them instantly. We meet businesses where they are, not where software wants them to be.

We have many customers, strong revenue growth, years of runway, and backing from world-class investors. I’ll share more once we meet.

About the Role

As an ML Research Engineer at Maple, you'll be a part of our core product team transforming cutting-edge research into production-ready voice agents, serving millions of interactions for local businesses. Collaborate with experts from Google Brain, Two Sigma, Stanford, MIT, Columbia, and IBM, rapidly deploying advanced models and systems that directly impact small businesses.

We work in person, 5 days a week in our NYC office. Collaboration here is fast, noisy (in the best way), and high-trust. We move quickly, break things intentionally, and fix them just as fast.

What You'll Do

Optimize speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS) for real-world use, ensuring accuracy in diverse, noisy environments.

Fine-tune LLMs with retrieval-augmented generation (RAG), reinforcement learning (RL), and prompt engineering for dynamic, context-aware conversations.