Research Intern – Reinforcement Learning (RL) - Onsite

Job description

🚀 Build the next generation of Agentic AI with us Our platform combines conversation intelligence, multimodal understanding, and agentic AI systems to power both human agents and autonomous AI agents across the entire customer experience lifecycle. A core part of this vision is our investment in custom Small Language Models (SLMs) —purpose-built for CX workflows—paired with reinforcement learning systems that continuously improve decision-making in real-world environments. We’re looking for a Research Intern (Reinforcement Learning) to join us in shaping this future. What you’ll do: Design and build reinforcement learning environments that model real-world customer interaction workflows. Design RL agents that learn from these environments using real-world interaction data, rewards, and feedback loops Define reward models and feedback loops using real-world signals (outcomes and human feedback) Enable learning from production data by structuring interaction traces into training-ready datasets for offline and online learning Experiment with multi-agent systems and simulation frameworks for complex coordination and decision-making Collaborate with engineering and product teams to depl...