🛠 Tech Stack

💼 About This Role

You'll design and iterate on next-generation AI agents using cutting-edge RL/post-training methods at a well-funded startup ($20M). You'll bridge research and infrastructure, translating ambiguous objectives into clear technical requirements.

🎯 What You'll Do

• Advancing agent capabilities by designing and iterating on AI agents for real workloads.
• Building robust infrastructure for reliable, efficient, and massive-scale agent operation.
• Prototyping agents and eval harnesses for real-world use cases and external systems.
• Designing novel RL and post-training methods to align models with domain-specific tasks.

📋 Requirements

• Strong background in machine learning engineering with experience in post-training, RL, or alignment.
• Experience with agent frameworks like DSPy, LangGraph, MCP, or Stagehand.
• Familiarity with distributed training/inference frameworks such as vLLM, sglang, Accelerate, Ray, or Torch.
• Track record of research contributions in ML/RL via publications or open-source work.

✨ Nice to Have

• Web programming experience (React, TypeScript, Next.js).
• Experience running LLM evaluations or synthetic data generation.
• Experience deploying containerized systems at scale (Docker, Kubernetes, Terraform).

🎁 Benefits & Perks

• 💰 $150k-$300k cash compensation plus equity.
• 🏖️ Flexible work (San Francisco or hybrid-remote).
• 🛂 Visa sponsorship and relocation support.
• 📚 Professional development budget.
• 🌍 Team off-sites and conference attendance.