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Lead Machine Learning Engineer

Saris · Toronto; San Francisco

Extracted from the posting

Base
Not stated
Equity
Equity package offered; amount not stated
Remote
Based in San Francisco, Montreal and Toronto
Funding
Backed by Tier 1 Silicon Valley VCs; amount not stated

Lead Machine Learning Engineer owning the ML/AI function end-to-end, including architecture of multi-modal agentic AI systems for banking workflows. Responsibilities include evaluation frameworks, productionizing ML systems for reliability and compliance, and building an ML team. Requires 8+ years of ML/AI engineering with technical lead or manager experience, and LLM/agentic systems experience.

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, 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 If You

  • 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

Why Join Saris 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 customers
  • 🐦 🔥Our team is backed by Tier 1 Silicon Valley VCs
Saris
Saris
Website

Job details

TypeFull-time
Work ModeHybrid
LevelLead
Location🇨🇦Toronto, ON🇺🇸San Francisco, CA🇨🇦Montreal, QC
PostedNov 06, 2026
Apply Now

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