We are seeking a Research Engineer to join a university-level research centre collaborating with industry. The position is for one year, renewable subject to satisfactory performance. Successful candidates will be involved in a project that is related to generative design.

Key Responsibilities:

• Deploy, optimize, and integrate generative AI models onto edge devices, ensuring efficient performance in real-world applications.

• Develop robust pipelines and frameworks for AI model inference on edge platforms, considering hardware constraints and latency requirements.

• Optimize AI models for power efficiency, memory footprint, and computational speed, utilizing techniques like quantization, pruning, and model distillation.  

• Conduct thorough testing, debugging, and performance validation of deployed models under various real-world conditions.

• Work closely with researchers, data scientists, and software engineers to bridge the gap between research prototypes and deployable solutions.

Job Requirements:

• Master’s degree or above in Computer Science, Electrical Engineering, Artificial Intelligence, or a related discipline.

• Bachelor’s degree holders with relevant industry experience are also encouraged to apply.

• Strong background in machine learning and deep learning, particularly in generative AI models.

• Proficiency with relevant programming languages and frameworks such as Go, Python, C++, and CUDA.

Additional Criteria:

• Industrial experience in relevant areas such as AI deployment, edge computing, or R&D is desirable.

• Ability to work independently with limited supervision and collaborate effectively within a multidisciplinary team.

• Strong problem-solving skills and the ability to adapt to hardware constraints and real-world challenges.

• Familiarity with edge computing platforms (e.g., NVIDIA Jetson, ARM Cortex, and mobile chipsets) and related tools.

We regret that only shortlisted candidates will be notified.