Research Engineer, Discovery

Overview

Research Engineer, Discovery works end-to-end across the model stack to identify and remove infrastructure blockers for training, evaluation, and deployment of advanced AI systems (“AI scientist”).

What you'll do

• Design and implement large-scale infrastructure for AI scientist training, evaluation, and deployment across distributed environments.
• Identify and resolve infrastructure bottlenecks that impede progress toward scientific capabilities.
• Develop robust evaluation frameworks to measure progress toward scientific AGI.
• Build scalable VM/sandboxing/container architectures to safely execute long-horizon AI tasks and workflows.
• Translate experimental requirements into production-ready infrastructure through collaboration.
• Develop and optimize large-scale data pipelines for advanced language model training and reinforcement learning workloads.

What you'll need

• 6+ years of highly-relevant experience in infrastructure engineering with expertise in large-scale distributed systems.
• Deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads.
• Experience with containerization technologies (Docker, Kubernetes) and orchestration at scale.
• Proven track record building large-scale data pipelines and distributed storage systems.
• Ability to work across the full ML stack from data pipelines to performance optimization.
• Strong communication and collaborative teamwork skills.

Details

• Hybrid policy expects staff to be in an office at least 25% of the time.
• Visa sponsorship is available; not guaranteed for every role/candidate.