Qualifications

• Strong machine-learning engineering skills with emphasis on coding and system building.
• Proficiency in Node.js, Python, React, and TypeScript with solid Kubernetes and Docker experience.
• Ability to thrive in a high-ownership startup culture with a focus on fast-paced work.
• Proven track record of significant contributions in prior roles.
• Experience or research background in reinforcement learning is beneficial but not mandatory.
• Bachelor's degree in computer science or similar field, or equivalent practical experience.

Responsibilities

• Design and construct RL environments that accurately reflect real-world scenarios.
• Develop and refine agents for specific tasks until they are efficient and ready for production.
• Collaborate with the research team to identify and prioritize future environment needs.
• Manage backend and infrastructure components to ensure reliability and scalability of environments.
• Establish engineering standards in the emerging RL function as the team expands.

Benefits

• Remote work flexibility within the United States.
• Opportunity to work with a newly formed, talented RL team.
• Clear growth trajectory as the team scales with industry needs.
• Potential for uncapped profit sharing based on performance.
• Engagement in innovative work that blends research and practical application.