Research Engineer - Reinforcement Learning

About the Role

As a Research Engineer in our Reasoning team, you'll play a crucial role in shaping our technological direction, focusing on our test-time compute scaling research ideas. This role is ideal for individuals who enjoy working with synthetic data and teaching LLMs reasoning abilities. You will be contributing to Prime Intellect's mission of building the open superintelligence stack, from frontier agentic models to the infrastructure that enables anyone to create, train, and deploy them. This involves aggregating and orchestrating global compute into a single control plane and pairing it with a full RL post-training stack, including environments, secure sandboxes, verifiable evals, and an async RL trainer.

Responsibilities

• Lead and participate in novel research to build a massive scale synthetic data generation pipeline and orchestration solution.
• Optimize the performance, cost, and resource utilization of AI inference workloads by leveraging the most recent advances for compute & memory optimization techniques.
• Contribute to the development of our open-source libraries and frameworks for synthetic data generation and distributed RL frameworks.
• Publish research in top-tier AI conferences such as ICML & NeurIPS.
• Distill highly technical project outcomes in layman approachable technical blogs to our customers and developers.
• Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, synthetic data generation research and proactively identify opportunities to enhance our platform's capabilities and user experience.

Requirements

• Strong background in AI/ML engineering, with extensive experience in designing and implementing end-to-end pipelines for the inference or training of large-scale AI models.
• Deep expertise in distributed inference techniques and frameworks (e.g., vllm, sglang) for optimizing the performance and scalability of AI workloads.
• Solid understanding of MLOps best practices, including model versioning, experiment tracking, and continuous integration/deployment (CI/CD) pipelines.
• Passion for advancing the state-of-the-art in reasoning and democratizing access to AI capabilities for researchers, developers, and businesses worldwide.