Lead Machine Learning Engineer

United States Digital Space LLC; Toronto; On-site; CAD 180,000 - 240,000; Full time

Benefits offered by this job

Equity package

Premium benefits

Job summary

AI, a Toronto-based AI startup, is seeking an ML Engineering Lead to own the ML/AI function end-to-end. You will set technical direction, architect multi-modal agentic systems, and drive production-ready deployments in real-world banking workflows.

Ideal candidates have 8+ years in ML/AI, deep experience with LLMs, and a proven track record leading initiatives from problem definition to production. This role offers equity and a fast-paced, early-stage environment.

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 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 Engineering

LLMs

Agentic systems

Team leadership

Production ML

Job description

About the company AI

We\u2019re a San Francisco, Montreal and Toronto based applied AI startup that\u2019s 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\u2019s 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\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 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 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 customers


• Our team is backed by Tier 1 Silicon Valley VCs