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.

Responsibilities

- 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.

Qualifications

- 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 to 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.

Bonus Points

- Experience building agentic systems, orchestration layers, or long-context reasoning systems.
- 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.

Benefits

- 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 perks 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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📌 Lead Machine Learning Engineer (Toronto)
🏢 Doist
📍 Toronto