As a Research Engineer at Metis, you’ll work on building the next generation of autonomous post-training systems that leverage our Mantis platform. You’ll operate at the intersection of cutting-edge ML research and scalable engineering, designing, implementing, and deploying algorithms that improve how AI agents learn from feedback, synthetic data, and real-world interactions.

You’ll move seamlessly between papers and production, leading large-scale experiments, creating optimized training pipelines, and helping shape the future of post-training autonomy. You’ll have significant ownership, high compute budgets, and the mandate to push the state of the art in applied reinforcement and preference optimization.

What You'll Do

Research and help build an autonomous post-training agent leveraging the Mantis platform
Design and execute large-scale experiments on synthetic data generation and algorithmic architecture
Develop and refine methods for reinforcement learning, reward modeling, and human feedback integration
Collaborate cross-functionally with Core and Platform Engineering to deploy and evaluate models in production settings
Publish or contribute to leading-edge research in the post-training domain
Use tooling and compute efficiently to iterate on experimental pipelines and accelerate research velocity