About Quotient AI

At Quotient, we are building an end-to-end evaluation platform for AI. We believe that model evaluation is essential to shipping successful AI products quickly and confidently. We enable researchers and developers to understand the tradeoffs they are making in training and deploying AI models and products. With Quotient, they can iterate faster towards more ambitious goals.

Quotient will enable AI products to become ubiquitous, reliable, and safe.

As AI applications expand in reach and complexity, we are committed to staying on the bleeding edge of understanding the quality, responsibility, and performance of AI, from inception to deployment.

Our founders most recently led AI evaluation for GitHub Copilot. We have raised a Seed Round from top VCs and angel investors.

About the Position

We are looking for experienced engineers who understand AI systems, and are excited about becoming global leaders in a completely novel field. We need people that can work independently as part of a small team.

You will be responsible for building the industry’s first end-to-end AI evaluation platform, starting with an offline evaluation harness and web platform. You’ll also help forge the foundation of our company’s engineering team and company culture.

We are a small team passionate about technology, research, and the extraordinary things we can build when we combine the two. We’re also fun, collaborative, and have meaningful lives outside of work.

You might be a good fit if you’ve worked as an ML engineer, data engineer, or full-stack engineer on ML-backed products. We are building a team in Boston, Massachusetts, and preference will be given to candidates who can join us in our office 2 days per week.

What you’ll do:

• Work closely with the CTO and lead early product development, including designing and implementing a foundational evaluation platform.
• Balance trade-offs for performance and usability for our initial customers. We want our platform to be easy to use, and for customers to get results fast.
• Ship to learn: iterating, experimenting, and testing ideas to move us along our path to product-market fit.
• Bootstrap our initial development processes, tooling, and infra.
• Collaborate with external researchers, design partners, and early customers.

Requirements:

• ≥ 5 years of full time industry experience building production systems, with experience using deep learning frameworks like PyTorch, Tensorflow, or related libraries
  • Alternatively: demonstration of a deployed system you scaled up leveraging open-source tools
• You’re a self-starter who is comfortable with ambiguity and open-ended technical challenges
• You can independently own projects end-to-end, from ideation to production
• You can balance building high quality software with prioritizing company goals
• Experience with different cloud providers like AWS, GCP, or Azure

Nice to have (but not required):

• Experience with ML systems, particularly high scale distributed inference for modern LLMs
• Experience with Typescript / React or some frontend framework
• Experience building user-facing data, ML, or analytics products
• Experience working at an early stage startup
• Familiarity with data warehouse solutions like Databricks or Snowflake

Benefits

• Competitive VC-backed startup salary: $175K to $225K
• Equity-stake in the company
• Medical, dental, and vision insurance
• 401k benefits
• Unlimited PTO policy & holiday shutdown last week of the year
• Paid commuter benefits for employees working hybrid in Boston
• Weekly team lunches and dinner

Unfortunately, we’re currently unable to sponsor visas.