Lead Machine Learning Engineer

Doist; Toronto; On-site; CAD 140,000 - 220,000; Full time

Job summary

Saris AI in Toronto is seeking a senior ML leader to steer the ML/AI function across the company, shaping technical direction and standards for multi-modal agentic systems used in banking workflows. You will drive end-to-end ML initiatives, align teams, and uphold reliability and compliance in live deployments.

As a hands-on leader, you will mentor engineers, guide architecture decisions, and push for scalable, production-ready solutions in fast-moving, ambiguous settings with high ownership.

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.

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.

Skills

ML leadership

Lead ML initiatives

Agentic systems

Deep learning

Transformers

MLOps

People leadership

Tools

RAG

Open-source LLMs

Closed LLMs

Monitoring tools

Job 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.

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 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.