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