About the job
About Saris AI
At Saris AI, we are an innovative applied AI startup with offices in San Francisco, Montreal, and Toronto, dedicated to redefining the banking industry's approach to automation. Our mission is to address complex automation challenges that necessitate long-context reasoning, tool orchestration, and agentic decision-making, all while ensuring reliability and compliance.
We have successfully deployed real agents that manage actual customer workflows in production settings. As we experience significant growth and revenue traction, we are eager to expand our engineering team to enhance our existing solutions and explore new possibilities.
Our core engineering team is on the lookout for a Senior Machine Learning Engineer who thrives in dynamic, early-stage environments.
Your Responsibilities
- Develop and maintain the ML infrastructure that ensures the reliability and continuous improvement of our AI systems, including evaluation frameworks, prompt management, and model observability.
- Consistently deliver customer-facing AI features while balancing new capabilities with essential infrastructure work.
- Define and implement the team's strategies for evaluations, large language model routing, prompt engineering, and model selection.
- Create practical standards that enhance quality without hindering team productivity.
- Contribute to the technical direction of ML by highlighting trade-offs and architectural choices to guide informed decision-making.
Who You Are
- 4+ years of experience in machine learning or AI engineering, with a proven history of deploying production ML systems.
- Strong hands-on expertise with large language models (LLMs), prompt engineering, evaluations, and model routing.
- Experience in building tools and systems that deliver real value to customers.
- Pragmatic in making trade-offs; understands when 'good enough' is appropriate and avoids unnecessary over-engineering.
- Comfortable navigating ambiguity and capable of taking a scoped problem, working through it, and delivering a solution.
- Focuses on the end user; recognizes the impact of ML decisions on customers and prioritizes customer value over technical perfection.
- Enhances team dynamics through code reviews, collaborative work, and effective communication regarding technical decisions.
Bonus Points If You
- Have experience in regulated industries, particularly banking.

