Tech Stack

Description

You will work end-to-end to identify and address key blockers on the path to scientific AGI, focusing on improving models' abilities to use computers as a laboratory for long-horizon tasks. You will develop approaches for complex reasoning, scale research ideas from prototype to production, and create benchmarks for evaluating model capabilities in scientific workflows.

Requirements

• 8+ years of ML research experience
• Familiarity with large-scale language model training, evaluation, and inference
• Experience with performance optimization and distributed computing
• Ability to translate research concepts into scalable engineering solutions
• Track record of shipping ML systems for multi-step reasoning problems

Responsibilities

• Identify and remove bottlenecks to scientific AGI across the full stack
• Develop approaches for long-horizon task completion and complex reasoning
• Scale research ideas from prototype to production
• Create benchmarks for model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimizations