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ABOUT POOLSIDE

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.

Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.

ABOUT OUR TEAM

We were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration (and croissants) in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.

Our team is a multidisciplinary blend of research, engineering, and business experts. What unites us is our deep care for what we build together. We're in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we've assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has. By building collaboratively and with intention, we create a compounding effect that moves the entire company forward towards our mission: reaching AGI through intelligence systems built for software development.

ABOUT THE ROLE

The Interfaces team builds the product surfaces for Poolside’s Model Factory: our industrial approach to the process of training models. Your role is to turn parts of model training – experiments, trajectories, evals, data inspection – into a product that can be easily seen and interacted with.

You'll join as a full-stack product engineer and own surfaces end-to-end, from backend and APIs to the web UI, for the researchers and engineers who build our models. You'll figure out what they actually need, ship fast, and iterate on quickly on feedback, balancing scalability and flexibility. Much of this work is greenfield: whole areas are still untouched or require complete revamps. Since researcher velocity and ability to make decisions with limited time and resources are critical to our success, your work will directly accelerate Poolside's ability to develop models.

YOUR MISSION

To deliver the product surfaces and platform that make poolside's model-building process visible, usable, and fast for the teams who build our models.

RESPONSIBILITIES

Own product surfaces end-to-end, from backend services and APIs to the web UI, across the Model Factory platform
Turn the opaque parts of model training (experiments, trajectories, evals, data inspection) into interfaces people trust and use every day
Deeply understand the needs of applied researchers; align closely on their use-cases, find the bottlenecks, and ship new platforms + features to improve their workflows
Build the platform other internal teams contribute their own UI into (a.k.a. our internal design system)
Quickly iterate on feedback, prioritizing adoption and usability
Uphold quality across the stack: performance, reliability, and high-utility interfaces

SKILLS & EXPERIENCE

Strong full-stack product engineering: you build end-to-end, from data model to polished web UI
Product sense: you have an intuition for what users need, can make product decisions independently, and deeply care about the products you build
Fluent in a modern web stack (e.g. TypeScript / React) and a backend language, comfortable anywhere in the stack
You thrive in ambiguity and greenfield work, taking a loosely-defined problem all the way to a shipped, adopted product
Low ego, collaborative, and fast-moving; you do your best work close to research, product, and infrastructure

Nice to have:

A working understanding of how ML models are built (experiments, evals, training workflows), or real curiosity to learn it
Experience with data-analysis tooling, agent tooling, or AI products

We encourage you to apply even if you do not believe you meet every single qualification.