Platform Research Engineer

The role As a platform research engineer, you'll build the core AI systems that make Applied Compute's platform intelligent. This includes our memory system, continual learning infrastructure, agent-building tooling, scaling synthetic environments & evaluations, and integrating the RL stack that powers agent improvement over time. You'll serve as the connective tissue between our AI product engineers (who build the interfaces and tools customers use) and our applied research engineers (who work directly with customers to ship agents into production). Your job is to take learnings from across customer deployments, identify the greatest common denominators, and build ML-grounded platform capabilities that make every delivery better. What you'll do Build and improve the memory refinery: the algorithms and systems that allow agents to learn continuously from production traces and company data Develop and maintain trace search, trace mining, and data labeling systems that feed the continual learning loop Research and implement approaches to multi-agent system design, including structuring agent coordination and managing trade-offs Build best in class coding agents for automatically creating initial agents for delivery and hill-climbing harnesses Translate learnings from applied research and customer deployments into generalizable platform features Collaborate closely with AI product engineers to ensure new ML capabilities are integrated into polished platform experiences What we're looking for Strong software engineering fundamentals combined with deep ML/AI knowledge Experience building systems that involve LLMs in production: prompt engineering, structured outputs, RAG, or agent frameworks Clear research experience: including top-tier conference publications, blogs, or reports Strong experimental design skills: you are diligent, don't cut corners, and actually run experiments Highly organized: you manage complexity across multiple workstreams Ability to read and translate research papers and prototypes into shippable engineering Strong candidates also have Experience with reinforcement learning, RLHF, or similar human-in-the-loop learning systems Background in building evaluation frameworks, benchmarks, or data quality systems Experience with continual learning, memory systems, or knowledge distillation Opinions about multi-agent system architectures and the trade-offs between different approaches Published work or open-source contributions in AI/ML systems Previous experience as a founder or early engineer at a zero-to-one company About us Applied Compute builds Specific Intelligence for the enterprise. We provide the continual learning infrastructure for companies to build agent workforces trained on proprietary data and institutional expertise. Our researchers and platform embed directly within customer environments to build custom evals, train models, and deploy agents that get better with use. Why we’re excited: We get to work at a rare intersection. Our product team builds the platform powering a new generation of digital coworkers. Our research team pushes the frontier of post-training and reinforcement learning. Our applied AI team sits side-by-side with customers as they ship agents into production. This combination of strong product, deep research, and boots on the ground is what we believe it takes to bring AI to the enterprise. We are product-led, research-enabled, and forward-deployed. Who we are : We’re a team of engineers, researchers, and operators. Many of us are former founders. We've built RL infrastructure at OpenAI, data foundations at Scale AI, and systems at Together, Two Sigma, Watershed, and others. We work with F50 customers and are fortunate to be backed by partners like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks. Who Thrives Here : We're looking for people who are excited about applying novel research and complex systems to real-world problems. Our team genuinely enjoys working with customers: listening, empathizing, and understanding how work actually gets done in their organizations. Former founders, people who've built a lot of side projects, or anyone who's shown they can own something end-to-end, tend to do well here. Benefits & Logistics This role is based in San Francisco. We work from our office in the Mission. We offer: Competitive compensation and equity Generous health benefits Unlimited PTO Paid parental leave Daily lunches and dinners Transportation and relocation support Retirement plans We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification. As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.