About the company AIWe U2019re a San Francisco, Montreal and Toronto based applied AI startup that U2019s building the future ofwork in the banking industry. We are tackling a $100 billion/yr problem, doubling every quarter and pushing the boundaries of what U2019s possible with multi-turn AI agentic systemsOur 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 U2019ve shipped real agents that handle real customer workflows in production. With a growing customer base and live deployments, we U2019re 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 U2019ve led ML systems from v1 to scale, and enjoy defining both the technical direction and the systems that power them.Your mission is toOwn and lead the ML/AI function end-to-end, setting technical direction and standards across the companyArchitect and guide the development of multi-modal, agentic AI systems powering real-world workflowsDefine and oversee evaluation frameworks, datasets, and performance metrics to continuously improve agent qualityDrive productionization of ML systems, ensuring reliability, scalability, and compliance in real-world environmentsBuild and mentor a high-performing ML team over time, setting best practices across modeling, experimentation, and deploymentWho You Are8+ years of experience in ML/AI engineering,



including time as a technical lead or managerProven track record of leading ML initiatives end-to-end, from problem definition production deploymentDeep experience with LLMs and/or agentic systems, ideally in real-world, customer-facing applicationsStrong understanding of ML fundamentals (deep learning, transformers, model evaluation, tradeoffs)Experience scaling ML systems in production, including monitoring, iteration, and reliabilityDemonstrated ability to lead engineers, influence architecture decisions, and drive technical directionComfortable operating in early-stage, ambiguous environments with high ownershipStrong communication skills with the ability to translate complex ML concepts into explicit decisionsBonus Points If YouHave experience building agentic systems, orchestration layers, or long-context reasoning systemsAre 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 performanceWhy Join the company AI?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 customersOur team is backed by Tier 1 Silicon Valley VCs#J-18808-Ljbffr

📌 Lead Machine Learning Engineer (Toronto)
🏢 United States Digital Space
📍 Toronto