Research Engineer Intern

Job description

Pluralis Research works on Protocol Learning: training and serving large models in a fully decentralized way on small consumer-grade devices connected via the internet. Despite being dismissed as infeasible, we have made significant advances on this problem, most recently Agora, a permissionless run that pretrained an 8B model from scratch on consumer GPUs spread over the internet, with no single participant ever holding the full weights ([tech report](https://arxiv.org/abs/2607.13332)). While many of the core research problems have been solved, Protocol Learning unlocks a series of new challenges. For the mission in full, read [A Third Path: Protocol Learning](https://pluralis.ai/blog/a-third-path-protocol-learning/). As a Research Engineer Intern you'll work on Agora, our production decentralized training system, alongside the engineers running real multi-node training at scale. Intern projects are well-scoped pieces of our live roadmap, not side experiments: you'll ship real work in week one and own a genuine open problem by the end of your internship. ## Key Responsibilities - **Ship a roadmap project**: Design, build, and ship a well-scoped project on the Agora roadmap, with a final presentation to the engineering and research teams. - **Concurrent and parallel systems**: Build and improve multiprocessing, async I/O, and threading components inside a production distributed training stack. - **Training infrastructure**: Work hands-on with large-scale training infrastructure across cloud providers (AWS/GCP). - **Daily production work**: Contribute to the production codebase every day, with code review and mentorship from a buddy on the Agora team. ## What We're Looking For - **ML background (required)**: Current enrollment in, or recent completion of, a Masters or PhD in machine learning, computer science, or a related field. You can keep pace with a research-driven team, not just a strong generalist engineering profile. - **Strong engineering**: Strong Python and PyTorch, and experience building concurrent or parallel systems: multiprocessing, async I/O, threading. - **Distributed ML exposure**: Hands-on exposure to distributed machine learning via internship, coursework, or serious projects, and experience with AWS, GCP, or other hyperscalers. - **Mission alignment**: You believe Protocol Learning is the viable third path for collective, trustless, and sovereign AI. ## Nice to Have - Top-tier ML publications (welcome, but not required for systems-focused candidates). - Open-source contributions to ML frameworks, distributed systems, or networking libraries. ## FYI's - This is a full-time, fixed-term internship: 3 months, with the option to extend. Australia-based candidates only. - We work remotely across the world, with the main teams in Australia and North America. You'll need to be comfortable working across timezones. - Applicants must have professional-level English proficiency (written and spoken). - Recruiters: we aren't looking for agency support at this time. We'll reach out if we need help. *We are backed by* [*Union Square Ventures*](https://www.usv.com/) *and other tier-1 investors, and we are a world-class, deeply technical team of ML researchers. Pluralis is unapologetically ideological. We believe AI, and the world, end up on a better path if we succeed in implementing the protocol for intelligence. If this resonates, please apply.*