Research Scientist

OpenKrill; United States; On-site; USD 160,000 - 240,000; Full time

Benefits offered by this job

Equity-Heavy Package

Remote-First Culture

Visa Sponsorship

Relocation Support

Job summary

Pluralis Research seeks a Research Scientist to advance Protocol Learning and train frontier models across distributed consumer hardware. You will publish and present findings, and work with engineers to deploy results in ongoing training runs.

You will contribute to an equity-heavy package, remote-first culture, and visa sponsorship/relocation options to Australia or the US.

Qualifications

• PhD in ML with top-tier conference publications (NeurIPS, ICML, ICLR).
• Hands-on distributed ML experience at scale.
• Strong PyTorch programming skills.

Responsibilities

• Address open problems in Protocol Learning and scaling across diverse hardware.
• Publish results in Tier-1 venues and integrate findings into live training runs.
• Collaborate with engineering to deploy research outcomes in production systems.

Skills

Distributed ML

PyTorch

Research publications

Education

PhD in machine learning

Tools

PyTorch

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/.

This setting breaks nearly every assumption of datacenter training and inference: communication‑efficient training across different parallelism axes, fault tolerance as nodes join and drop mid‑run, heterogeneous compute and networks, and robustness to malicious participants. Our published methods include Subspace Networks https://arxiv.org/abs/2506.01260, Factored Gossip DiLoCo https://arxiv.org/abs/2606.22768, AsyncMesh https://arxiv.org/abs/2601.22442, and Sentinel https://arxiv.org/abs/2603.03592.

As a Research Scientist you work on the problems that stay open as we push from the 8B run toward frontier scale, and you publish what you find. These are foundational papers up for grabs.

KEY RESPONSIBILITIES

• - Solve the open problems: Identify the questions that block Protocol Learning at scale. communication efficiency, convergence under churn and staleness, heterogeneity, robustness to malicious participants.
• - Publish in Tier-1 venues: The problems are hard and largely unclaimed. Solve them, and publish.
• - Get the methods into runs: Work with the engineering team so your results land in live training runs, not just papers.

WHAT WE'RE LOOKING FOR

• - Research excellence (required): PhD in machine learning with publications in top‑tier conferences (NeurIPS, ICML, ICLR).
• - Distributed ML experience: Hands‑on experience in large‑scale distributed training and compression strategies.
• - Implementation skills: Strong programming ability in PyTorch.
• - Mission alignment: You believe Protocol Learning is the viable third path for collective, trustless, and sovereign AI.

NICE TO HAVE

• - Experience with foundation model pre‑training, post‑training, or RL.
• - Experience at proprietary, open‑weight and open‑source AI labs

COMPENSATION & BENEFITS

• - Equity-Heavy Package: We offer significant ownership for key technical contributors in addition to a high base salary.
• - Remote-First Culture: Flexible work environment with team members distributed globally.
• - Visa Sponsorship: Optional full visa sponsorship and relocation support to either Australia or the US.
• - Open Problems: Training and serving frontier models on hardware you don't control, over networks you don't own, mostly has no published answers yet. You'll write some of the first ones.

FYI'S

• - 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).

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 view AI and the world on a better path for everyone if we are able to implement the protocol for intelligence.