Reinforcement Learning
Job Summary:
We are looking for a Senior Reinforcement Learning Engineer to lead the development and integration of RL algorithms within our AI-driven placement engine. This role involves enhancing our AI capabilities by incorporating RL strategies for optimal decision-making and utilizing insights from Large Language Models to enrich training data and scenarios.
Key Responsibilities:
Develop and optimize reinforcement learning models that drive our AI-based placement engine, improving efficiency and accuracy in furniture arrangement and space utilization.
Integrate LLM outputs to augment and enhance the training datasets for RL models, ensuring a rich, context-aware learning environment.
Lead projects to test and scale RL solutions, ensuring they meet the functional and performance criteria required for real-world applications.
Collaborate with cross-functional teams, including NLP engineers and design experts, to ensure that RL models effectively incorporate domain-specific knowledge and customer preferences.
Stay updated with the latest research and technologies in RL and LLMs, applying best practices and innovations to advance our AI capabilities.
Required Qualifications:
Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
Minimum of 5 years of experience in developing and deploying reinforcement learning systems.
Proven track record with modern RL techniques and frameworks (e.g., RLLib, TensorFlow Agents).
Experience in integrating outputs from Large Language Models into reinforcement learning training environments.
Strong programming skills in Python and familiarity with AI development environments.
Desirable Skills:
Experience working with NVIDIA’s AI platforms and tools.
Published research in reinforcement learning, particularly in applications related to spatial planning or related industries.
Demonstrated ability to work collaboratively in a team-oriented environment.