Panoptive
The oversight engine for clinical trials
Research Engineer Intern
About the role
Note: This is a fall/winter internship only.
The Role:
You will work directly with the founders on advancing the product roadmap and AgentHub’s core evaluation and simulation capabilities. You’ll have significant scope and will keep up to date with the latest state-of-the-art methodologies and techniques across areas like agent evaluation, data generation, and RL - translating these into real features in the hands of real users.
What you will do:
- Design and build the core methodologies and components for evaluating agents across axes like instruction following, safety, groundedness, and efficiency
- Research, experiment, and implement robust data generation capabilities
- Tie in the latest advancements in research and productionalize them to unlock value for our customers
Signs you might thrive in this role:
- Working towards a Bachelors/Masters/PhD in Computer Science or related field
- Passionate about building category-defining products
- Previous background and experience in reinforcement learning
- Demonstrated experience in model/agent evaluation is a major plus
- Opinionated, perpetually curious, and love having scope over a problem and delivering
About Panoptive
At AgentHub, we’re building the simulation and evaluation engine for AI agents. As agents become more powerful, complex, and widely deployed, the need to efficiently and thoroughly evaluate them grows significantly. Our platform enables teams to measure safety, reliability, and quality by testing agents in realistic environments, surfacing insights, and driving improvements.
We’re an early seed-stage startup, built by the former tech lead of Apple’s Foundation Model Evaluation team and CMU and MIT grads and backed by Y-Combinator, leading VC’s, and angels.
Joining AgentHub means working directly with the founders on high-impact problems, shaping the culture, and building the critical infrastructure layer that will make complex, agent-driven products possible. If you want to work at the frontier of AI, where research meets real-world systems, we'd love to hear from you.
