Goodfire is seeking a research engineer to lead the development of their model training infrastructure, focusing on transforming pre-trained models into safe, capable, and reliable AI systems through fine-tuning, RLVR, and other post-training techniques.
Requirements
- 4+ years of experience in ML engineering, with at least 2 years focused on LLMs or foundation models
- Deep expertise in fine-tuning, RLVR, and modern post-training techniques
- Production experience deploying and maintaining language models at scale
- Technical proficiency in Python, PyTorch/JAX, and distributed training frameworks
- Expert understanding of supervised fine-tuning, RLVR, DPO
- Experience with preference modeling and reward model training
- Hands-on experience with parameter-efficient fine-tuning (e.g., LoRA, QLoRA)
Responsibilities
- Design and implement scalable and customizable post-training pipelines (SFT, RLVR, DPO)
- Develop suitable evaluation frameworks
- Optimize inference-time interventions and model serving for post-trained models
- Collaborate with research teams to rapidly prototype and validate new techniques
Other
- Put mission and team first
- Improve constantly
- Take ownership and initiative
- Action today
- Mission alignment with building safe and powerful AI systems
