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.
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Reinforcement Learning Engineer at fast-growing AI infrastructure startup
Are you ready to shape the future of RLOps? We are looking for a Reinforcement Learning Engineer to build a first-of-its-kind platform for training and deploying RL models at scale. You'll work on cutting-edge open-source frameworks, enjoy a 6-month remote work policy, and receive significant stock options in a well-funded AI startup. If you have deep expertise in PyTorch and distributed computing, this is your chance to lead the development of industrial-grade RL infrastructure in London.
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Location
London, United Kingdom
Compensation
Not Disclosed + Equity
Company
Confidential company
Role overview
About the company
Fast-growing AI infrastructure startup
What you will do
- 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.
Who this is a fit for
- 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.
Why this role is remarkable
- 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.
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If your profile’s a match and Confidential company wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.