Location: San Francisco, CA or Leuven, Belgium (hybrid)

Start date: January 2027

Job Description

Belfort's mission is simple: make computing on encrypted data possible. We are leading the field, working with partners like Google and NVIDIA, and Jeff Dean is one of our early backers. Our technology runs mostly on GPUs, and one of its biggest use cases is AI: running large language models on data that stays encrypted the whole time.

We are looking for an LLM Researcher to help us build and train models that work well on encrypted data. This is a research role with hands-on engineering. You will own work across the full training pipeline, from pretraining to post-training, running on large GPU clusters. You will work closely with our cryptography and engineering teams to shape models that are both accurate and efficient under encryption.

Responsibilities

Training Pipelines

• Build, run and improve pretraining and post-training pipelines on large GPU clusters
• Scale training jobs across many GPUs and nodes, and keep them fast and stable
• Find and fix bottlenecks in data loading, memory use, communication and throughput
• Build evaluation pipelines to track model quality throughout training

Model Research

• Pretrain and post-train language models, including fine-tuning, instruction tuning and preference optimization (RLHF, DPO or similar)
• Adapt transformer architectures so they run efficiently on encrypted data
• Use scaling laws to plan experiments and decide where compute is best spent
• Design, run and analyze experiments, and turn results into clear decisions
• Publish and present work where it fits our roadmap

Collaboration