Senior Reinforcement Learning Research Scientist

About the Company: ShopperAI is a fast-growing retail tech start-up specializing in decision-making analytics for the physical retail world. Our innovative solutions empower retailers with valuable insights into customer behavior, enabling them to optimize their operations and drive revenue growth. We are committed to leveraging cutting-edge technologies like reinforcement learning, computer vision, and cloud-native services to deliver state-of-the-art solutions that transform the retail industry.

We seek an experienced and passionate Senior Reinforcement Learning Research Scientist to join our growing team at ShopperAI. As a Senior RL Research Scientist, you will be a key contributor to developing our next-generation solutions, applying your expertise in reinforcement learning and related fields to enhance our decision-making analytics platform. You will work closely with cross-functional teams, including software developers, data scientists, and product managers, to design, implement, and optimize algorithms that drive meaningful insights from complex retail datasets.

Responsibilities:

• Conduct cutting-edge research and development in multi-agent reinforcement learning to solve complex retail analytics and decision-making problems.
• Work closely with data scientists to ensure proper data collection, preprocessing, and feature engineering to support RL research and development.
• Analyze experimental results, conduct performance evaluations, and iterate on models and algorithms to drive continuous improvement.
• Contribute to developing technical documentation and research papers to showcase our advancements and intellectual property.

Requirements:

• MSc or Ph.D. in Computer Science, Electrical Engineering, or a related field, focusing on reinforcement learning or machine learning.
• Experienced research scientist with a strong understanding of multi-agent reinforcement learning.
• Familiarity with multi-agent systems.
• Expertise in deep learning frameworks such as TensorFlow, PyTorch.
• Strong programming skills in Python and proficiency in relevant libraries and tools for RL research and development.
• Experience in implementing RL algorithms.
• Solid understanding of the theory and principles of reinforcement learning, including Markov decision processes, value iteration, policy gradients, Q-learning, and deep Q-learning.
• Familiarity with cloud-native solutions and services, such as AWS, Azure or Google Cloud.
• Demonstrated ability to work in a fast-paced, startup environment with a proactive and problem-solving mindset.
• Excellent communication and collaboration skills, with the ability to effectively present and discuss complex ideas and research findings with technical and non-technical team members.
• Advantage: publication record, leading conferences and journals related to reinforcement learning.

Benefits:

• Competitive salary and equity options.
• Comprehensive health insurance coverage.
• Flexible work hours and a supportive work environment.
• Opportunity to significantly impact the retail industry by driving innovation through reinforcement learning research.
• Professional development and learning opportunities.
• Collaborative and inclusive culture, fostering innovation and creativity.