Are you passionate about driving innovation through machine learning? Do you thrive in building and optimizing RL systems? If so, we have an exciting opportunity for you as a founding team member and Reinforcement Learning Scientist at fast growing incubation.  

We’re currently looking for creative, smart people who want to join our team of world-renowned researchers as we push the boundaries applying AI to complex problems. As a Senior Analyst specializing in Reinforcement Learning, you will be at the forefront of driving the development and optimization of our RL models. You will play a crucial role in building and training Reinforcement Learning Models and designing feedback systems to continuously improve their performance. If you're a forward-thinking, technically adept individual with a passion for machine learning, this role is for you.   

Responsibilities:  

• Integrate with an interdisciplinary team of experts in optimization and simulation to design, build, and optimize models to deliver high-quality, real-world results.  
• Design and implement novel RL algorithms and approaches to solve complex problems, ensuring efficiency and scalability.  
• Develop and implement feedback mechanisms to continuously improve the accuracy and effectiveness of RL models.  
• Stay up-to-date with the latest advancements in reinforcement learning and implement best practices to enhance our ML infrastructure.  
• Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.  
• Collaborate with cross-functional teams to understand business requirements and translate them into actionable ML solutions.  

Requirements:  

• Proven experience in a leadership role driving RL system development and optimization.  

• Demonstrated expertise in building RL models for complex real-world problems and building robust training pipelines.  
• Extensive experience implementing reinforcement learning in complex domains – preferably with multi-agent systems or models that require temporal abstraction. 
• Proficiency in programming languages like Python, Java or C++ and the ability to write efficient, clean, and maintainable code.  
• Excellent written and verbal communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.  
• A Master's degree in Computer Science, Engineering, or a related field. A Ph.D. with a focus in Reinforcement Learning or a relevant area with a publication history is ideal.  
• U.S. citizenship is required  

Benefits:  

• Competitive salary and performance-based bonuses.  

• Comprehensive health and wellness benefits package.  
• Flexible work hours.  
• Opportunities for professional development and continued learning.  
• Collaborative and inclusive work environment.