Research Engineer, Production Model Post-Training

Requirements:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities

• Adapt quickly to changing priorities

• Maintain clarity when debugging complex, time-sensitive issues

• Have strong software engineering skills with experience building complex ML systems

• Are comfortable working with large-scale distributed systems and high-performance computing

Nice to Haves:

• Have experience with training, fine-tuning, or evaluating large language models

• Can balance research exploration with engineering rigor and operational reliability

• Enjoy collaborating across research and engineering disciplines

• Can navigate ambiguity and make progress in fast-moving research environments

• Have experience with LLMs

What You'll Be Doing:

• Implement and optimize post-training techniques at scale on frontier models

• Conduct research to develop and optimize post-training recipes that directly improve production model quality

• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation

• Develop tools to measure and improve model performance across various dimensions

• Collaborate with research teams to translate emerging techniques into production-ready implementations

• Debug complex issues in training pipelines and model behavior

• Help establish best practices for reliable, reproducible model post-training

Perks and Benefits:

• Public benefit corporation headquartered in San Francisco

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues