We're a San Francisco, Montreal and Toronto based applied AI startup that's building the future of work in the banking industry. We are tackling a $100 billion/yr problem, doubling every quarter and pushing the boundaries of what’s possible with multi-turn AI agentic systems
Our goal is to tackle the type of automation problems that require long-context reasoning, tool orchestration across legacy systems, and strict compliance loops: the ones without known answers.
We’ve shipped real agents that handle real customer workflows in production. With a growing customer base and live deployments, we’re scaling up fast and looking for deeply technical builders who want to have outsized impact early.
Our core engineering team is looking for a hands-on ML Engineering Lead who thrives in early-stage, ambiguous environments. You’ve led ML systems from v1 to scale, and enjoy defining both the technical direction and the systems that power them.
Own and lead the ML/AI function end-to-end, setting technical direction and standards across the company
Architect and guide the development of multi-modal, agentic AI systems powering real-world workflows
Define and oversee evaluation frameworks, datasets, and performance metrics to continuously improve agent quality
Drive productionization of ML systems, ensuring reliability, scalability, and compliance in real-world environments
Build and mentor a high-performing ML team over time, setting best practices across modeling, experimentation, and deployment
8+ years of experience in ML/AI engineering, including time as a technical lead or manager
Proven track record of leading ML initiatives end-to-end, from problem definition → production deployment
Deep experience with LLMs and/or agentic systems, ideally in real-world, customer-facing applications
Strong understanding of ML fundamentals (deep learning, transformers, model evaluation, tradeoffs)
Experience scaling ML systems in production, including monitoring, iteration, and reliability
Demonstrated ability to lead engineers, influence architecture decisions, and drive technical direction
Comfortable operating in early-stage, ambiguous environments with high ownership
Strong communication skills with the ability to translate complex ML concepts into clear decisions
Have experience building agentic systems, orchestration layers, or long-context reasoning systems
Are comfortable across the stack (data → modeling → infra → APIs)
Have worked with both open-source and closed LLMs, including fine-tuning or retrieval systems (RAG)
Have a strong product mindset and care deeply about real-world impact, not just model performance
🏦 Join us in building the future of work for the trillion-dollar banking industry using cutting edge AI technology.
⚡Tackle ambiguous technical challenges with no clear answers.
💲Competitive compensation with premium benefits and equity package.
🤝Work with a stellar team of engineers, builders, and leaders; including repeat YC founders with a successful exit (Ready Education).
📈We already have production agents live with revenue-generating customers
🐦 🔥Our team is backed by Tier 1 Silicon Valley VCs
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