Research Scientist: High-Performance AI & Edge Deployment

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

A*STAR RESEARCH ENTITIES is seeking a PhD-level researcher to lead optimization work for high-performance AI. You will explore QAT, pruning, distillation, and NAS to reduce latency while designing scalable AI deployment architectures for high-throughput camera and sensor data.

You will co-design hardware/software for deployment on Jetson/TensorRT/FPGAs and build asynchronous data pipelines, with rigorous benchmarking. Expect collaboration with SI and impact across manufacturing environments.

Qualifications

• PhD in Computer Engineering, Computer Science, Electrical Engineering or related field with HP AI focus.
• Minimum 3 years of experience in relevant tech and research roles.
• Deep understanding of AI inference engines and model compression techniques.
• Proficient in C++ and Python for high-performance implementation.
• Hands-on parallel computing with CUDA/OpenCL and mixed-precision deployment.

Responsibilities

• Lead research into optimization techniques (QAT, pruning, distillation, NAS) to minimize latency.
• Design scalable AI deployment architectures for multi-camera/high-throughput data streams.
• Co-design hardware/software for deployment targets (Jetson, TensorRT, FPGAs, accelerators).
• Develop asynchronous data pipelines from image acquisition to decisions.
• Establish performance benchmarks for latency and memory across environments.
• Collaborate with System Integrator to integrate models into factory software stack.

Skills

AI inference engines

Model compression

C++

Python

Parallel computing

Mixed-precision training

End-to-end AI systems

Education

Ph.D. in Computer Engineering/CS/EE or related field (High-Performance AI)

Tools

TensorRT

ONNX Runtime

OpenVINO

CUDA

OpenCL

Job description

A*STAR RESEARCH ENTITIES is seeking a PhD-level researcher to lead optimization work for high-performance AI. You will explore QAT, pruning, distillation, and NAS to reduce latency while designing scalable AI deployment architectures for high-throughput camera and sensor data.

You will co-design hardware/software for deployment on Jetson/TensorRT/FPGAs and build asynchronous data pipelines, with rigorous benchmarking. Expect collaboration with SI and impact across manufacturing environments.