Lead Machine Learning Engineer

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Description

About Saris AI 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. Your mission is to 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 Who You Are 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, in

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