Research Engineer Turn routing, fine-tuning, and alignment research into production behavior. Remote · San Francisco

Run BiOS runs serverless inference across the major open model families and fine-tunes custom models on dedicated GPUs. As a Research Engineer you improve the models themselves — from bios-adaptive, our automatic router across the model pool, to the fine-tuning methods and alignment recipes customers run. You turn research into behavior that serves production traffic.

• Develop and evaluate routing strategies for bios-adaptive across the open-model pool, and measure what they do to quality, latency, and cost.
• Design fine-tuning and alignment recipes — SFT, LoRA/QLoRA, DPO-family objectives, continued pre-training — that behave predictably on dedicated-GPU infrastructure.
• Build evaluation harnesses that catch regressions before customers do.
• Read the literature, reproduce what matters, discard what does not, and ship what wins.
• Work with product engineering to make research outcomes visible and controllable in the product.
• Write down what you learn — internal notes, docs, and occasionally public posts.

• At least 5 years in machine learning engineering or research, with meaningful time on large language models.
• Hands-on experience fine-tuning open-weight models:
  PyTorch, distributed training, parameter-efficient methods.
• Evaluation rigor: when you say a model got better, you can show how you know.
• Engineering fundamentals strong enough that someone else can reproduce your experiments.