at Quotient AI
Boston, MA / NYC / SF / Hybrid or Remote
About Quotient AI
Created by members of the team that built the evaluation infrastructure of GitHub Copilot, Quotient is grounded in first-hand knowledge of what is needed to create and ship powerful generative AI products.
Quotient connects the dots between intention and outcome in LLM product development. And through rapid, data-driven experimentation grounded in real-world scenarios, Quotient enables developers to evaluate, improve and ship high-quality AI products through rapid, real-world, data-backed experimentation. Quotient's tools power AI product evaluation with specialized datasets and frameworks, which can be customized or ready-to-use, and tailored to specific use-cases and organizations. By addressing challenges in evaluation management, version control, and orchestration, Quotient streamlines assessments of models, prompts, and retrieval augmentation.
With Quotient, developers can build better AI products fast.
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, Infrastructure Engineer, or SRE. 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 engineering team 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 tooling, infrastructure, and deployment processes
- Collaborate with external researchers, design partners, and early customers.
Requirements:
- 5 years of full time industry experience building and operating production systems in a modern cloud / enterprise setting, using tools like Python, terraform / pulumi, or kubernetes / lambda — with security in mind
- You’re a self-starter who is comfortable with ambiguity and open-ended technical challenges
- You can own projects end-to-end, and effectively collaborate with teammates
- You can balance building high quality, secure 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 building user-facing data, ML, or analytics products
- Experience working at an early stage startup
Benefits
- Competitive salary and equity stake in the company
- Medical, dental, and vision insurance
- 401k benefits with company match
- Unlimited PTO policy & holiday shutdown last week of the year
- Paid commuter benefits for employees working hybrid in Boston
- Weekly team lunches
Unfortunately, we’re currently unable to sponsor visas.
Interested? Get in touch!
Email careers@quotientai.co with your resume or an online profile, and how you think you can contribute to Quotient’s success.
