Reinforcement Learning Engineer at fast-growing AI infrastructure startup

You will lead the development of a first-of-its-kind RLOps platform, designing scalable infrastructure for RL model training and LLM finetuning. By integrating advanced machine learning frameworks into an open-source ecosystem, you will provide critical tools for businesses to deploy reinforcement learning models effectively while staying at the forefront of AI research.

Fast-growing AI infrastructure startup

• Design and implement the architecture for a scalable RLOps platform and a robust open-source RL framework.
• Integrate diverse ML libraries and environments to support advanced model training, deployment, and lifecycle management.
• Stay current with the latest RL and MLOps advancements to incorporate cutting-edge algorithms into the platform's core.

• Holds a Master's or Ph.D. in Computer Science or has 3+ years of industry experience in reinforcement learning.
• Possesses deep expertise in PyTorch, Ray, or Gym, along with a strong background in hyperparameter optimization.
• Has proven experience building machine learning tooling, cloud-based distributed infrastructure, and production deployment pipelines.

• Opportunity to build pioneering RLOps infrastructure and open-source tools from the ground up in a high-impact field.
• Join a well-funded venture backed by top-tier VCs at the intersection of reinforcement learning and production-ready MLOps.
• Benefit from a highly flexible work environment with 6-month remote policies and a dedicated annual learning budget.