Demonstrate strong hands-on experience in AWS cloud engineering and cloud-native architectures, including compute, container, serverless, networking, storage, database, security, monitoring and integration services, with the ability to independently design, provision, deploy, troubleshoot, secure and optimise AWS solutions;
Work closely with the Project Manager to develop project schedules, monitor progress, and implement corrective measures to ensure deadlines are achieved.
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.
Work regularly with engineers to engage in conversations regarding their performance, professional growth, offering constructive feedback, mentoring, and guidance as needed.
In-charge of test case(s) creation and execution and work with product engineering team to ensure features are developed correctly and meet acceptance criteria
Fine-tune open-weight large language models and vision-language models (supervised fine-tuning, Low-Rank Adaptation and its quantised variant) on domain data.