Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to enable real-time decision-making.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Leads and coordinates the creation, curation, simplification, sourcing and localisation / translation of learning; leads the renewal, updates and consolidation of learning content; and provides support and guidance to Squads on critical quality assurance activities and managing escalated risks and issues.
Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
Classroom Maintenance: Work with teachers to maintain the classroom environment, facilities and other resources for maximum engagement of students in their learning
Own delivery end to end in fast, agile iterations, from turning an ambiguous problem into a clear plan, through design and development, to successful deployment and operation of features, data, and models in production.
Own delivery end to end in fast, agile iterations, from turning an ambiguous problem into a clear plan, through design and development, to successful deployment and operation of features, data, and models in production.