Member of Engineering (Experiment Platform) - poolside

ABOUT POOLSIDE In this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search... 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. 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. 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. 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. PROCESS - Intro call with one of our Members of Engineering - Technical Interview(s) with one of our Members of Engineering - Team fit call with the People team - Final interview with one of our Founding Engineers BENEFITS - Fully remote work & flexible hours - 37 days/year of vacation & holidays - Health insurance allowance for you and dependents - Company-provided equipment - Wellbeing, always-be-learning and home office allowances - Frequent team get togethers - Great diverse & inclusive people-first culture