Research Scientist - Geo-Distributed Inference
Pluralis Research3 hours ago
Responsibilities
- Own the inference stack end to end, including pipeline-parallel execution, placement and routing, transport, serving-engine internals, and failure handling.
- Design, validate, and productionize new algorithms for fast inference on consumer hardware over the public internet.
- Keep the rollout pipeline fast and reliable for reinforcement-learning training and evolve it into a serving layer for trained models.
Requirements
- Hands-on experience shipping serving-engine internals or building a large-scale inference system.
- Research ability demonstrated through publications, blog posts, or unpublished work in distributed inference or related fields.
- Experience with low-bandwidth, high-latency systems operating over networks such as the public internet.
- Belief in Protocol Learning as a decentralized, trustless, and sovereign approach to AI.
- Professional-level written and spoken English proficiency.
- Familiarity with RL post-training, Apple silicon or MLX, P2P networking, NAT traversal, or work at proprietary, open-weight, or open-source AI labs is preferred.
Benefits
- Significant equity ownership in addition to a high base salary for key technical contributors.
- Remote-first work environment with globally distributed team members.
- Full visa sponsorship and relocation support to either Australia or the US.
- Work on open research problems in training and serving frontier models across hardware and networks the company does not control.
- Applicants should be comfortable working across time zones.
Categories
About Pluralis Research
Pluralis Research builds a protocol and tooling for collaborative, decentralized training and ownership of foundation models, enabling training and serving across heterogeneous, consumer-grade devices over the internet. The team demonstrated Agora, a permissionless run that pretrained an 8B model from scratch without any single participant holding the full weights. The privately held company is backed by Union Square Ventures and focuses on developer-facing infrastructure for large-scale model training and serving.