ML Systems Engineer Intern — GPU Pipelines & Trading

SIG; Hong Kong; Sur place; HKD 110 000 - 165 000; Plein temps

Résumé du poste

Susquehanna is offering a 10-week Machine Learning Engineering Internship in Hong Kong. You’ll build and optimize training pipelines on our GPU cluster, work on inference for production trading systems, and develop the data infrastructure behind our research efforts.

A mentorship-driven internship emphasizes real-world impact and cross-team collaboration. Eligible candidates are pursuing a degree in CS/ML/EE (or related fields) with strong Python and C++, plus hands-on ML experience

Qualifications

• Pursuing a Bachelor's, Master's, or PhD in computer science, machine learning, electrical engineering, mathematics, physics, statistics, or a related field. Intend to graduate and start full-time by August 2028.
• Strong programming skills in Python, comfort with C++.
• Hands-on experience with ML frameworks such as PyTorch or JAX beyond API usage.
• Exposure to distributed training, GPU programming, orchestration, or large-scale data processing.

Responsabilités

• Build and optimize training pipelines across GPU infrastructure, including distributed training for large models.
• Work on inference and deployment—latency, throughput, and cost in production trading systems.
• Develop data infrastructure for research, moving large market datasets through ingestion, storage, and transformation.
• Profile and benchmark ML workloads; contribute to internal libraries and tools.

Connaissances

Python programming

C++ programming

GPU programming

System design

Formation

Bachelor's/Master's/PhD in CS/ML/EE

Outils

PyTorch

JAX

CUDA

Triton

CuTe DSL

Description du poste

Susquehanna is offering a 10-week Machine Learning Engineering Internship in Hong Kong. You’ll build and optimize training pipelines on our GPU cluster, work on inference for production trading systems, and develop the data infrastructure behind our research efforts.

A mentorship-driven internship emphasizes real-world impact and cross-team collaboration. Eligible candidates are pursuing a degree in CS/ML/EE (or related fields) with strong Python and C++, plus hands-on ML experience