Lead Machine Learning Engineer

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