🛠 Tech Stack

💼 About This Role

You'll work at the intersection of frontier post-training methods and real-world agent systems, advancing how models are aligned and deployed. By designing next-gen agents and building robust evaluation pipelines, you'll directly shape product direction and research priorities. This is a customer-facing role with a fast-moving team backed by Founders Fund.

🎯 What You'll Do

• Design and iterate on next-generation AI agents for real workloads
• Build distributed evaluation pipelines and coordination frameworks
• Translate customer needs into technical requirements for RL and eval teams
• Rapidly prototype agents and eval harnesses alongside customers

📋 Requirements

• Strong background in machine learning engineering with post-training or RL experience
• Experience with applied data workflows and evaluation frameworks for large models or agents
• Deep expertise in distributed training/inference frameworks (e.g., vLLM, sglang, Ray, Accelerate)
• Track record of research contributions (publications, open-source) in ML/RL

✨ Nice to Have

• Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform)
• Passion for advancing reasoning and building practical agentic AI systems

🎁 Benefits & Perks

• 💰 Equity incentives
• 🏖️ Flexible work (remote or San Francisco)
• 🌍 Visa sponsorship & relocation support
• 📚 Professional development budget
• 🎉 Team off-sites & conference attendance