Lead Machine Learning Engineer
- Role
- AI / ML
- Experience
- Lead
- Employment
- Full-time
- Company size
- Startup
Open to GB, CA only. Set where you work from to check your eligibility.
No BS summary
Lead-level ML engineer with 8+ years in ML/AI, including technical lead or manager experience. Needs deep LLM and/or agentic systems experience and production ML scaling experience. Hiring remotely in the United Kingdom and Canada.
Core skills
Optional skills
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
What you'll do
- 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.
What they require
- 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, including deep learning, transformers, model evaluation, and 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.
- Preferred: Experience building agentic systems, orchestration layers, or long-context reasoning systems.
- Preferred: Comfortable across the stack from data to modeling to infrastructure to APIs.
- Preferred: Experience working with both open-source and closed LLMs, including fine-tuning or retrieval systems.
- Preferred: Strong product mindset and care deeply about real-world impact, not just model performance.
Benefits
- 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.
- Production agents already live with revenue-generating customers.
- Backed by Tier 1 Silicon Valley VCs.
- Opportunity to build the future of work for the banking industry using cutting edge AI technology.
- Tackle ambiguous technical challenges with no clear answers.
Saris AI is a San Francisco, Montreal and Toronto based applied AI startup building AI agentic systems for automation in the banking industry.