Member of Engineering (Experiment Platform)

Remote (EMEA/East Coast)

ABOUT POOLSIDE

In this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will determine who survives and wins. 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 and engineering at scale. They will create powerful economic engines. 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.

poolside exists to be one of these companies - to build a world where AI will drive the majority of economically valuable work and scientific progress.

We believe that software development will be the first major capability in neural networks that reaches human-level intelligence because it's the domain where we can combine Search and Learning approaches the best.

At poolside we believe our applied research needs to culminate in products that are put in the hands of people. Today we focus on building for a developer-led increasingly AI-assisted world. We believe that current capabilities of AI lead to incredible tooling that can assist developers in their day to day work. We also believe that as we increase the capabilities of our models, we increasingly empower anyone in the world to be able to build software. We envision a future where not 100 million people can build software but 2 billion people can.

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ABOUT OUR TEAM

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

ABOUT THE ROLE

You'll sit at the intersection of Poolside's research, infrastructure, and agent teams, building a greenfield platform that democratises how every frontier model gets built. The Experiment Platform team owns the API gateway and the research services behind research velocity and experiment lineage. In a given week, you might design the data models and API contracts behind experiment intent, ship the CLI researchers use daily, or connect the platform to training and eval pipelines. If you want to own a foundational platform, work alongside the people building frontier models, and help shape where research infrastructure goes next, this is the role for you.

YOUR MISSION

To build a reliable, scalable Experiment Platform that ties Poolside's research systems together, and improves how every model gets built.

RESPONSIBILITIES

Design and build robust backend services primarily using Python and Go to power our API Gateway and Experiment Platform.
Partner closely with researchers, infrastructure teams, and agent platform engineers to translate research workflows into intuitive APIs, data models, and developer experiences.
Drive adoption of agent-native research workflows by delivering the Experiment CLI.
Integrate with existing research infrastructure and build dashboards to track adoption and usage metrics.

SKILLS & EXPERIENCE

Proven experience building production APIs, distributed systems, or platform infrastructure.
Strong engineering fundamentals across backend architecture, API and database design, and operational excellence.
Demonstrated ability to lead ambiguous, cross-functional initiatives, aligning stakeholders around a shared technical vision.
Nice to have: Understanding of ML research workflows, including experiments, training runs, evaluations, checkpoints, configurations, datasets, and research iteration cycles.