Research Engineer – Pre-training

Job not on LinkedIn

🔥 15 hours ago

🌐 United States, Australia – Remote

🇺🇸 United States – Remote 🇦🇺 Australia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📚 Research Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Pluralis Research

WebsiteLinkedInAll Job Openings

1 - 10 employees

🤖 Artificial Intelligence

🌐 Web 3

Artificial Intelligence • Web 3

Pluralis Research is a foundational AI research lab focused on Protocol Learning — decentralized, multi‑participant training of foundation models where no single participant holds a full copy of the model. The group develops methods to enable communication‑efficient model and pipeline parallelism, unextractable collaborative models, and high‑compression context parallelism so community‑trained, community‑owned frontier models can scale over low‑bandwidth, internet‑connected devices. Their work targets practical systems and algorithms that make decentralized training competitive with centralized training while enabling new ownership and economic models.

📋 Description

• Implement and optimize model-parallel distributed pretraining across data, pipeline, and tensor parallelism • Train large models on heterogeneous GPUs over low-bandwidth, high-latency internet links • Implement techniques to reduce communication overhead while maintaining model convergence • Build elasticity and fault tolerance for node churn, including checkpointing, state synchronization, and participant recovery • Build run instrumentation and monitoring for throughput, bottlenecks, and model quality across hundreds of devices • Take Protocol Learning from an 8B model run to frontier scale

🎯 Requirements

• Hands-on experience training models across many devices in PyTorch using FSDP, DeepSpeed, Megatron, or an equivalent implementation • Understanding of data, tensor, and pipeline parallelism • Production-quality Python • Experience with concurrency, failure handling, and profiling before optimizing • Evidence of shipped systems, research code, open-source work, or serious personal projects • Professional-level English proficiency, written and spoken • Comfortable working across time zones • Nice to have: experience training or serving large language models such as Nemotron, Qwen, or OLMo • Nice to have: experience with P2P networking and NAT traversal • Nice to have: experience with post-training and reinforcement learning • Nice to have: experience with inference and serving systems • Nice to have: experience at proprietary, open-weight, or open-source AI labs

🏖️ Benefits

• Significant equity ownership in addition to a high base salary • Flexible remote work environment • Full visa sponsorship and relocation support to Australia or the US for exceptional candidates • Opportunity to work on open, frontier-scale research problems • Work with a globally distributed team