Own the engineering standard for the FDE track, including solution architecture patterns, engineering practices, testing, evaluation, production readiness and operational support requirements.
Collaborate closely with IT operations and DevOps teams to ensure the smooth integration of infrastructure platforms with other applications and processes.
Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.; Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, TensorFlow, Keras etc.
Follow up on cutting-edge technologies such as global large model inference, GPU high-performance computing, distributed parallelism, and cache optimization, benchmark against mainstream inference frameworks such as vLLM and TensorRT-LLM, complete the implementation of solutions and technological innovation, continuously iterate and optimize the performance and cost advantages of the inference system, and build the core technological barriers of the team.
Operate and extend the Studio engine: image generation (gpt-image-2), video generation (Seedance 2.0 via BytePlus), reference-anchored character consistency, take/cut/release pipelines
Job Description: dConstruct is looking for robotics engineers to join our vibrant and driven systems integration team working on solving challenging problems in robotics. As a robotics engineer you will be developing our robotics software stack and helping to perform software integration for specific use cases. You will be coding, calling into our software stack and creating applications which utilise our software stack to meet the needs of clients. You will be working with clients to understand their needs and, in turn, implement their requirements accordingly.
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.
AISG is a national initiative driven by the Ministry of Digital Development and Information (MDDI), the Infocomm Media Development Authority (IMDA), and the National Research Foundation, Singapore (NRF).
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.