Mid-Training Research Engineer — Scientific LLMs

Doist; Menlo Park (CA); On-site; USD 250,000 - 350,000; Full time

Job summary

Doist is seeking a Midtraining Research Engineer to advance scientific reasoning in frontier models. You will curate data, generate synthetic datasets, and build robust evals while enabling scalable, GPU-driven training experiments.

The role supports pre-training groundwork and requires hands-on distillation techniques and scalable tooling. You will collaborate with RL researchers, scientists, and engineers to push data-driven breakthroughs and improve model intelligence in science-focused

Qualifications

• Bachelor's degree or equivalent experience required.
• Experience training LLMs at scale is essential.
• Ability to design and evaluate scientific reasoning data.

Responsibilities

• Identify, process, and curate novel sources of scientific data for large-scale model training.
• Generate high-quality synthetic data to fill gaps in scientific knowledge.
• Build evaluations that correlate with downstream scientific task performance.
• Develop and apply techniques such as self-distillation and on-policy distillation.
• Design and run large-scale training experiments, partnering with supercompute engineers to scale across thousands of GPUs.
• Build tools to study how data choices shape model intelligence.

Skills

LLM training

Data curation

Large-scale training

Eval design

Distributed training

Education

Bachelor's degree or equivalent

Tools

PyTorch

TensorFlow

Job description

Doist is seeking a Midtraining Research Engineer to advance scientific reasoning in frontier models. You will curate data, generate synthetic datasets, and build robust evals while enabling scalable, GPU-driven training experiments.

The role supports pre-training groundwork and requires hands-on distillation techniques and scalable tooling. You will collaborate with RL researchers, scientists, and engineers to push data-driven breakthroughs and improve model intelligence in science-focused