Espresso (translucence Research Inc) jobs

Sales Development Representative New York Office, Brooklyn, New York, United States About Espresso AI 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 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. About the Role A Sales Development Representative at Espresso is a hands-on, high-effort position for someone who learns fast and is comfortable iterating rapidly in a metrics-based environment. You'll spend most of your time prospecting and booking high-quality demos with technical and financial decision-makers. Expect a lot of autonomy, a lot of learning, and a lot of travel. If you're extroverted, curious about technical products, and excited by the idea of building something from the ground up, this role is for you. We're very early, which means you have the chance to make a big impact; substantially exceed quota (and earn a lot!); and progress fast to AE. What You'll Work On - Proactively prospecting new accounts through cold calling, cold emailing, LinkedIn, and other creative outbound approaches - Booking qualified demos with data

Staff Infrastructure Engineer New York Office, Brooklyn, New York, United States About Espresso AI 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. 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. 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 a highly technical role with deep systems work at its core. What You'll Work On - Design, build, and scale Espresso's distributed execution and scheduling systems - Develop internal compute environments to safely offload workloads from Snowflake and Databricks - Implement compiler-style analysis and optimization of SQL workloads - Build infrastructure and data pipelines that support ML modeling and product features -

Staff ML Engineer New York Office, Brooklyn, New York, United States Train cutting-edge models to optimize our users' compute costs.

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