Software Engineer

Magic's mission is to build safe AGI that accelerates humanity's progress on the world's most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.About the roleAs a Software Engineer at Magic, you will work on core systems or product surfaces that directly determine model capability and user experience.This role can map onto Pre-training Data, RL Research & Environments, or Product, depending on background and strengths. Across all placements, the expectation is end-to-end ownership: defining problems, implementing solutions, shipping to production, and iterating based on real outcomes.Magic's long-context models introduce unique technical challenges — internet-scale data acquisition, long-horizon post-training loops, and product workflows that make complex model behavior understandable and controllable. You will operate close to these constraints, building systems that are both technically rigorous and production-ready.This role can evolve into deeper specialization in data systems, post-training capability development, or product engineering leadership, depending on strengths and interests.What you'll work onDepending on team placement, you may:Build and scale large distributed data pipelines for pre-trainingDesign filtering, mixture, and dataset versioning systemsDevelop post-training datasets, evaluation frameworks, and reward pipelinesRun ablations that translate capability goals into measurable improvementsBuild end-to-end product surfaces that integrate deeply with the modelDesign APIs, backend services, and frontend workflows for AI-first experiencesImprove reliability, observability, and performance of production systemsWhat we're looking forStrong software engineering fundamentalsHigh ownership and comfort operating in ambiguous problem spacesExperience building production systems at scaleAbility to reason clearly about trade-offs between quality, performance, and costStrong technical judgment and bias toward shippingTrack record of turning complex technical problems into working systemsCompensation, benefits, and perks (US):Annual salary range: $200K - $550KEquity is a significant part of total compensation, in addition to salary401(k) plan with 6% salary matchingGenerous health, dental and vision insurance for you and your dependentsUnlimited paid time offVisa sponsorship and relocation stipend to bring you to SF, if possibleA small, fast-paced, highly focused teamMagic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience.Our cultureIntegrity. Words and actions should be alignedHands-on. At Magic, everyone is buildingTeamwork. We move as one team, not N individualsFocus. Safely deploy AGI. Everything else is noiseQuality. Magic should feel like magic