🛠 Tech Stack

💼 About This Role

You'll design and build reinforcement learning environments that model real-world customer interaction workflows. You'll define reward models using real-world signals and enable learning from production data. This internship offers direct exposure to 0→1 AI innovation in CX and decisioning systems.

🎯 What You'll Do

• Design and build RL environments for customer interaction workflows.
• Design RL agents using real-world interaction data and rewards.
• Define reward models and feedback loops from real-world signals.
• Structure interaction traces into training-ready datasets.
• Experiment with multi-agent systems and simulation frameworks.

📋 Requirements

• Pursuing a degree in Computer Science, AI, or related field.
• Strong understanding of reinforcement learning fundamentals.
• Familiarity with RL environments and training libraries like Verl and Tinker.
• Strong foundation in probability, math, and optimization.

✨ Nice to Have

• Experience with RLHF or LLM/SLM fine-tuning.
• Exposure to agent-based systems or multi-agent RL.
• Prior research or projects in RL or applied ML.

🎁 Benefits & Perks

• 🚀 Production-grade Agentic AI systems with leading enterprises.
• 🤝 Team with deep expertise from Amazon, Google, and Meta.
• 📈 Fast-growing Series C AI company.
• 💡 Direct exposure to 0→1 AI innovation.