ML Systems Engineer: Acceleration & Distributed Training

Motional; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

Motional is seeking a Machine Learning Systems Engineer to join the ML Acceleration team in Singapore. You will optimize training speed, reduce time-to-convergence, and build high-performance data pipelines and GPU kernels.

The role focuses on scaling large distributed models across compute resources and improving overall throughput. Ideal candidates have strong Python skills, deep PyTorch experience, and a solid foundation in ML concepts, architectures, and optimization strategies.

Qualifications

• Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.
• Strong proficiency in Python.
• Extensive hands-on experience with PyTorch.
• Experience optimizing ML model execution during training and inference; solid ML fundamentals.

Responsibilities

• Performance profiling to identify bottlenecks in data loading, gradient computation, and communication.
• Optimize distributed training pipelines using PyTorch Distributed.
• Design and maintain high-performance GPU kernels in Triton or CUDA.
• Design robust data loading pipelines to maximize training throughput.

Skills

Python

Problem Solving

Analytical thinking

Education

Bachelor’s/Master’s/PhD in CS or CE

Tools

Nsight

PyTorch Profiler

PyTorch

CUDA

Triton

Job description

Motional is seeking a Machine Learning Systems Engineer to join the ML Acceleration team in Singapore. You will optimize training speed, reduce time-to-convergence, and build high-performance data pipelines and GPU kernels.

The role focuses on scaling large distributed models across compute resources and improving overall throughput. Ideal candidates have strong Python skills, deep PyTorch experience, and a solid foundation in ML concepts, architectures, and optimization strategies.