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.
