Cut your Snowflake and Databricks bills in half with ML. Espresso AI uses machine learning to optimize your data warehouses in real-time. Backed by AI Grant.
About the role
As a Staff Infrastructure Engineer, you will design and build the distributed systems that power Espresso’s optimization engine. You will work across real-time scheduling, workload execution, performance analysis, and the internal compute environments that allow us to safely and efficiently offload warehouse workloads.
What they're looking for
- 7+ years software engineering experience
- Strong fundamentals in systems design, performance engineering, and debugging
- Ability to own complex technical projects end-to-end
- Comfort operating across a broad range of infrastructure challenges and tackling whichever problems are most critical to the system
More about this role
Espresso AI’s mission is to use machine learning to automate performance engineering. Today, we help our customers reduce Snowflake and Databricks SQL compute costs by up to 70%, unlocking massive efficiency gains without requiring any workflow changes.
More and more businesses are adopting data warehouses to manage invaluable data analytics workloads. Unfortunately, the costs of these workloads often grow exponentially over time, with no easy way for users to reduce cost — until now. Our next-generation, AI-based approach saves our users huge amounts of money.
We’re a well-funded, early-stage startup scaling quickly. Our most recent round was led by Nat Friedman and Daniel Gross.
As a Staff Infrastructure Engineer, you will design and build the distributed systems that power Espresso’s optimization engine. You will work across real-time scheduling, workload execution, performance analysis, and the internal compute environments that allow us to safely and efficiently offload warehouse workloads.
You will own major architectural components, drive reliability and performance improvements, and collaborate closely with founders and engineering on long-term technical direction. This is...
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