poolside

• Design, build, and operate the backend services, APIs, and orchestration systems that are the foundation for all our product experiences • Participate in on-call and incident response, as well as driving continual improvements to our reliability and operational posture • Collaborate across product, research, and engineering teams to deliver end-to-end product capabilities • Collaborate with solution architects to continually improve and streamline how we deploy the Poolside platform in on-premise environments

• Design, build, and operate a large-scale web crawler responsible for acquiring all openly accessible data on the internet • Develop specialized deep crawlers targeting high-value sources to improve recall and coverage • In collaboration with data researchers, own a long-term road map for data acquisition • Build observability, monitoring, and debugging tooling to ensure reliability and transparency across crawl infrastructure • Collaborate with pre-training, post-training, and evaluations teams to align data acquisition priorities with model training needs • Build high-throughput ingestion pipelines for rapidly onboarding partner data and evaluating it for quality

• Own product vision in 0-to-1 spaces, defining what Poolside should build and translating ambiguous problems into clear, buildable product direction. • Lead projects focused on research, experimentation, and proof-of-concepts, exploring what's next for developer tools and feeding insight back into Poolside's product direction. • Partner with leadership and engineering to make product decisions that hold up at both the strategic and the granular level. • Shape Poolside's external product presence, including our website and how developers first encounter our work. • Build the foundations of our developer marketing and evangelism function over time, helping us build community and excitement around what we're shipping. • Scale the design team as the company grows, hiring thoughtfully and keeping the bar high. • Lead and grow the design team across product and brand, providing feedback, direction, and the space for senior designers to operate autonomously.

• Own product vision in 0-to-1 spaces, defining what Poolside should build and translating ambiguous problems into clear, buildable direction. • Lead design, experimentation, and proof-of-concepts that explore what's next for developer tools, feeding insight back into the product roadmap. • Partner with Product Engineering to move ideas from concept to shipped product, working at both the strategic and the granular level. • Prototype rapidly and validate early; you're as comfortable in code as you are in a design tool. • Collaborate with designers and the wider design team to ensure product thinking is consistent and well-resourced across Poolside's surfaces. • Shape how Poolside shows up externally as a product, including how developers first encounter our work.

• Own the quality and consistency of Poolside's design across product, marketing, brand, and systems surfaces. • Build and evolve our design system; not just a component library, but a design pipeline that scales with the company. • Write reusable, production-quality frontend code: components and systems others can build on, not one-off pages. • Partner with Design Engineers on external-facing surfaces, ensuring brand and marketing reflect the same bar as the product. • Collaborate with Product Engineering to bring design system work into production and keep it alive as the product evolves. • Hold the visual bar across the team. Your taste and judgment should be raising the standard for everything around you.

• Research and experiment on ways to improve reasoning and code generation for LLMs. Own the full experiment life cycle from idea to experimentation and integration • Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation. Translate research ideas into clean, reusable codebases that other researchers can build on • Design, analyze, and iterate on data generation and training of LLMs • Implement and iterate on RL training pipelines that scale reliably across domains • Diagnose training instabilities and failures, debug RL runs and propose mitigation methods • Write high-quality, reproducible and maintainable code

• Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation • Develop methods for tuning training and inference end-to-end for high throughput • Design data control systems in an RL pipeline that govern what the model sees and when • Debug cases where infrastructure decisions are silently degrading learning dynamics • Build observability tooling that surfaces when a system-level issue is the root cause of a training regression • Help build robust, flexible and scalable RL pipelines • Optimize performance across the stack — networking, memory, compute scheduling, and I/O • Write high-quality, pragmatic code • Work in the team: plan future steps, discuss, and always stay in touch

• You will be the first point of contact for customers experiencing technical issues with our product. • You will troubleshoot, diagnose, and resolve technical problems. • The problems will range from issues in our SaaS offer to air-gapped on-prem deployments, where you’ll need to rely on the customer to be your eyes and ears. • You’ll need to be focused on creating the documentation, runbooks, and tools to help our support team scale efficiently. • You’ll be pivotal in promoting timely and professional technical support via support tickets and the occasional call.

• Research and experiment on ways to specialize foundational models to agentic use cases • Build and maintain data and training pipelines • Keep up with latest research, and be familiar with state of the art in LLMs, alignment, synthetic data generation, code generation • Design, analyze, and iterate on training/fine-tuning/data generation experiments • Write high-quality, pragmatic code • Work as part of a team: plan future steps, discuss, and communicate clearly with your peers

• Design a Python framework that makes it easy for poolsiders to implement both internal and public benchmarks in a centralized way • Build and maintain the pipeline that runs distributed evaluations at scale • Collaborate with modeling and product teams to identify opportunities to improve our experimentation and evaluation tooling