About the job
Saris AI develops applied AI solutions for the banking sector, with teams in San Francisco, Montreal, and Toronto. The company builds automation tools that handle complex, long-context reasoning and agent-driven decision-making. Reliability and compliance shape every product, and Saris AI's agents already manage real customer workflows in production. As revenue grows, the engineering team is expanding to enhance current offerings and explore new directions.
The Senior Machine Learning Engineer role is based in San Francisco and sits within the core engineering group. The team works in a collaborative, early-stage setting, balancing infrastructure needs with the delivery of features that serve customers directly.
What you will do
- Build and maintain machine learning infrastructure, such as evaluation frameworks, prompt management systems, and tools for model observability.
- Develop new AI features for customers while supporting and improving the underlying infrastructure.
- Shape strategies for evaluation, LLM routing, prompt engineering, and model selection.
- Set practical standards to boost quality without slowing down development.
- Guide technical direction by clarifying trade-offs and architectural choices.
Requirements
- Minimum 4 years of experience in machine learning or AI engineering, including production deployment of ML systems.
- Direct experience with large language models, prompt engineering, evaluation techniques, and model routing.
- Background in building tools and systems that deliver value to users.
- Comfort making pragmatic trade-offs and recognizing when a solution is sufficient.
- Ability to navigate ambiguity, define problems, and deliver results independently.
- Strong focus on end users and understanding the impact of ML decisions on customer experience.
- Supports team growth through code reviews, collaboration, and clear technical communication.
Bonus
- Experience in regulated industries, especially banking.

