Remote AI Research Engineer: LLM & Multi-Modal Pre-training

United States Digital Space LLC; United States; Remote; USD 120,000 - 210,000; Full time

Job summary

Tether is seeking a senior AI researcher to drive architecture development for large-scale LLM and multi-modal models in a fully remote role. You will lead pre-training efforts, optimize data pipelines, and push cross-modal capabilities with state-of-the-art transformer tech.

You will apply PyTorch and Hugging Face tooling, work on scalable distributed systems, and contribute to cutting-edge AI research that enhances precision and efficiency across platforms.

Qualifications

• PhD in NLP/ML with proven AI R&D track record.
• Experience building large-scale LLM or multi-modal pre-training.
• Strong knowledge of distributed training utilities.

Responsibilities

• Large-Scale Pre-Training: perform foundational pre-training for LLMs and multi-modal models on massive GPU clusters.
• Architecture & Alignment: design scalable architectures and cross-modal alignment layers.
• Data Strategy: curate massive text and multi-modal datasets; build data pipelines.
• Experimental Research: run experiments, analyze results, refine methods.
• Optimization & Debugging: identify bottlenecks in training efficiency and stability.
• System Scalability: advance distributed training systems for scalability.

Skills

LLM design

Multi-Modal

Pre-training

Transformer models

PyTorch

Hugging Face

Education

PhD in NLP/ML

CS degree

Tools

NVIDIA GPUs

Distributed training

Job description

Tether is seeking a senior AI researcher to drive architecture development for large-scale LLM and multi-modal models in a fully remote role. You will lead pre-training efforts, optimize data pipelines, and push cross-modal capabilities with state-of-the-art transformer tech.

You will apply PyTorch and Hugging Face tooling, work on scalable distributed systems, and contribute to cutting-edge AI research that enhances precision and efficiency across platforms.