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At AgileRL, we are on a mission to accelerate reinforcement learning for building superhuman artificial intelligence systems.

We believe that reinforcement learning will form a part of every sophisticated AI system of the future. It already impacts the world we live in, from its use in creating LLMs with reasoning capabilities, to enabling autonomous vehicles to make decisions. Reinforcement learning enables AI models to plan and achieve objectives, but currently very few companies or individuals have the resources to leverage this powerful machine learning paradigm.

AgileRL offers Arena, an enterprise-grade reinforcement learning operations (RLOps) platform and a state-of-the-art open-source framework to eliminate these barriers to entry. Our framework has already achieved 10x faster training and hyperparameter optimisation than leading RL libraries. Arena, built on top of our open-source framework, is focused on four key areas - simulation, training, deployment and monitoring.

We work closely with companies across industries including finance, defence, and technology to deliver best-in-class autonomous solutions. We are looking for talented engineers to join the team and develop the systems and tools that will enable the next wave of impactful AI.

As a member of the AgileRL team, you will have the opportunity to be at the forefront of reinforcement learning innovation. We value curiosity, creativity, and a passion for pushing boundaries. Together, we will build not only state-of-the-art software but also a culture of excellence, collaboration, and continuous learning.

We are seeking a talented and experienced Front-end Engineer to join our team and contribute to the development of a first-of-its-kind RLOps platform. As a Front-end Engineer, you will be responsible for designing, implementing, and maintaining the infrastructure, tools, and services that enable businesses to build and deploy reinforcement learning models efficiently and effectively.

Responsibilities:

• Develop scalable and reliable infrastructure to support a reinforcement learning model training, deployment, and management platform.
• Collaborate with the team to understand requirements, and design and develop the user-facing interface of the platform.
• Work closely with designers and engineers to implement the visual design elements within brand guidelines.
• Optimise the platform for speed and efficiency, minimising load times and ensuring a smooth user experience.
• Ensure that web content is accessible to all users by adhering to accessibility standards like Web Content Accessibility Guidelines.
• Working closely with users to identify and rectify user-facing bugs and issues to constantly improve the usability of the platform.
• Keeping thorough documentation of code and development processes to help maintain and troubleshoot the platform.

Requirements:

• Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or 3+ years of relevant industry experience.
• Proficient with front-end frameworks and libraries like ReactJS, Redux, GraphQL to streamline development and enhance user interactivity.
• Experience with integrating with various APIs (Rest API or GraphQL using one of fetch, Redux, Relay, GraphQL) to fetch and display data from external sources.
• Familiarity with tools for monitoring and improving platform page performance metrics, including page load times and resource optimisation.
• Deep understanding of software engineering principles and best practices.
• Strong problem-solving and communication skills, and the ability to work independently as well as in a team environment.

Compensation:

• Competitive salary + significant stock options.
• 30 days of holiday, plus bank holidays, per year.
• Flexible working from home and 6-month remote working policies.
• Enhanced parental leave.
• Learning budget of £500 per calendar year for books, training courses and conferences.
• Company pension scheme.
• Regular team socials and quarterly all-company parties.

AgileRL is an equal opportunities employer and welcomes applications from all qualified candidates. We are committed to creating a diverse and inclusive workplace.