Research Engineer
Core
Building experiments, debugging models, scaling training pipelines, and turning research ideas into working systems for frontier AI models.
Role type
Research Engineer (ML/NLP)
Builds
Production-ready research systems and infrastructure supporting large-scale model training and experimentation.
Domain
Artificial Intelligence / Natural Language Processing (NLP)
Deliverable
production ML models
Required skills
Deep learning frameworks (PyTorch), distributed training, model optimization, RLHF, finetuning, evaluation frameworks, clean code, system design, ablation analysis, rapid iteration
Preferred skills
Strong fundamentals in ML/NLP, curiosity, ability to translate research ideas into practical implementations
Technologies
PyTorch, distributed training, RLHF, finetuning, evaluation frameworks
Responsibilities
Build experiments, debug models, scale training pipelines, run large-scale experiments, implement new methods, analyze results, iterate quickly
Seniority
Individual Contributor (IC), mid-to-senior level