Machine Learning Systems Engineer

We are looking for an engineer with strong experience in GPU-accelerated machine learning and transformer-based models who also understands the systems and infrastructure side of ML workloads.

The ideal candidate can build, train, and optimize large-scale deep learning models while managing the hardware, GPU environments, and system operations required to run them efficiently.

Responsibilities

• Design, train, and optimize transformer-based models
• Build and maintain GPU training and inference environments
• Optimize GPU utilization, memory usage, and model performance
• Manage ML infrastructure including distributed training and GPU clusters
• Monitor and troubleshoot training jobs and system performance
• Work on scaling model training across multiple GPUs or nodes
• Collaborate with research and engineering teams to improve model performance and system efficiency

Qualifications

• Strong experience with Python and ML frameworks
• Experience working with transformer architectures (especially on FPGA)
• Solid understanding of GPU computing
• Experience with distributed training and large-scale datasets
• Familiarity with Linux systems and ML infrastructure
• Experience debugging performance bottlenecks in GPU workloads

Founded in 2016, Timeline Capital is a technology-driven quant firm specializing in algorithmic trading across Asian markets. At Timeline, we emphasize a flat organizational structure where ideas are openly shared, promoting innovation and success. We offer competitive salary packages and a supportive work environment, including tailored benefits like flexible working hours, free lunch and snacks, gym subsidies, and recreational facilities to ensure a healthy work-life balance.