Careers

We believe that AI will accelerate compute by 1000x.

Large Language Models are a fundamental breakthrough in AI: for the first time, models can deeply understand code in the same way that human programmers do. We believe that neural scheduling and optimization will leapfrog traditional optimization tools and usher in a paradigm shift in computation.

Espresso AI’s mission is to make this vision a reality.

Our first products focus on cloud data warehousing. Billions of dollars are spent on data warehousing compute annually, giving us an opportunity to advance our mission by delivering massive value to real customers.

We plan to expand to all major sources of compute.

Our team

Before Espresso, we built cutting edge NLU for Google Search & Siri, wrote exploits for web browsers, and saved Google staggering sums of money through performance engineering.

We have a high hiring bar - this will be the strongest group of engineers you've ever worked with.
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We're  early, so you will have a substantial equity stake and the opportunity to significantly impact the trajectory of this company.

Engineering

We're looking for exceptionally strong engineers driven to deliver customer impact. That can mean improving on the state-of-the-art in deep learning, but much more often it means figuring out why two libraries don't fit together, paying off technical debt, or reaching out to users to make their experience amazing.

We're looking for folks who are able to work autonomously, prioritize ruthlessly, and communicate effectively. We're prioritizing staff engineers with 5+ years of experience.

We expect you onboard and ship a meaningful feature in your first week.

Engineers in similar roles have built:

  • Consistent distributed systems
  • Optimal scheduling algorithms
  • High-quality visualizations
  • ML orchestration
  • Production monitoring systems
  • The worst regexes you’ve ever seen in your life

This isn't required, but let us know if you have prior experience with:

  • Small startups
  • Data warehouse cost optimization
  • SQL optimization
  • Software verification

If your colleagues would describe you as "the best engineer I've ever worked with", we'd love talk to you! You'll fit right in.

Sales

Our team is selling the future of cloud compute. We're looking for reps who are excited to get in the weeds with technical teams (and their finance counterparts) to help them understand what this future looks like and how Espresso will get them there.

You should be deeply interested in technology in general and AI specifically. Our customers are technical, which means you need to be technical too - a surface-level understanding isn't enough to build the trust you need to establish partnerships.

We have product market fit and multiple AEs closing deals, but we're still building out our sales process. As an early sales hire improving the process is a core part of your role. If you're expecting a well-oiled sales machine, we're not going to be a good fit - but if you're excited to have significant ownership and impact as we build from the ground up, we're at the perfect stage for you to join.

Office

Espresso AI is located in Brooklyn, NYC. We're in the office every day of the week. We’re happy to provide relocation.

What We Offer

  • Competitive salary and meaningful equity

    • Expected NY State pay range, Engineering: $150,000 - $300,000
    • 
Expected NY State pay range, Sales: OTE $100,000 - $300,000
  • Employee-friendly equity terms (early exercise)
  • Health, dental, and vision insurance
  • 401k with 4% match
  • Free salads & gym membership

Open Positions

Staff Distributed Systems Engineer

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Distributed systems engineers focus on scaling our distributed systems and building and scaling new ones (e.g. building out products for other data warehouses).

Brooklyn, NY
Full-Time

Staff Infrastructure Engineer

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Infrastructure engineers are responsible for shipping reliable production systems quickly. You will be scaling and improving our production environment, which includes real-time scheduling, optimization, and monitoring systems for data warehouses; offloading compute from data warehouses onto our internal environments; compiler-style optimization and analysis; data pipelines to run both the business and our machine learning projects; and our ML infrastructure.

Brooklyn, NY
Full-Time

Staff ML Engineer

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We are training cutting-edge models to optimize our users' compute costs. Our models need to answer questions like: how fast will this code run? Can this SQL query run faster on larger infra? Does this cluster have enough capacity for these workloads?

Brooklyn, NY
Full-time

We are a team of elite AI and performance engineers from Google, Apple, and MIT, and - starting with data warehousing- we are building the world’s first neural optimizer.

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