
Research Engineer Intern at Pluralis Research (Australia)
Pluralis Research· Australia·
Role details
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 arxiv.org/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 pluralis.ai
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 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.
Why work at Pluralis Research
- Culture of Radical Openness: The mission is to democratize AI ownership. Work here is published openly, and researchers contribute to a public good.
- High Impact, Small Team: With only 17 people, every hire has an outsized influence on shaping the protocol and company direction.
- Research First: The team is PhD-heavy and publishes at top-tier conferences (NeurIPS). The environment is scholarly and technically deep.
- Remote-Flexible (Hybrid): Presence in San Francisco (US) and Australia (largest cohort of 12 employees). The job postings do not mandate 5 days in-office; distributed collaboration is core to the product itself.
- Top-Tier Investor Backing: Backed by USV and CoinFund, providing strong financial runway and network effects in both the AI and crypto/Web3 ecosystems.
- Founding Team Pedigree: Work alongside former researchers from Anthropic, Google, and Amazon, creating a steep learning curve for ML engineers and scientists.