Software Engineer (Machine Learning)

TL;DR

Software Engineer (Machine Learning): Architecting and building mission-critical infrastructure to accelerate ML workflows and model iteration velocity, focused on foundational technology at the intersection of research and real-world systems. Focus on designing and implementing training pipelines, automated data workflows, and large-scale data collection systems.

Location: On-site in Hong Kong

Company

Our client is a leading creator of body motion video games that run on their own in-house developed device.

What you will do

• Lead the design and implementation of training pipelines, automated data workflows, and integration tooling.
• Build systems for large-scale data collection, preprocessing, and curation.
• Create tools to streamline experiment lifecycles and move models toward production.
• Collaborate with ML researchers to remove technical blockers and improve developer experience.
• Support model serving pipelines and integrate ML components with broader platform systems.

Requirements

• 3+ years experience building production-grade machine learning systems, data infrastructure, or research platforms.
• Deep hands-on expertise with Python and at least one systems language (e.g., C++, Go, Rust, Java).
• Experience with PyTorch or TensorFlow in production or research environments.
• Proven track record with ML training pipelines, data workflows, and integration tooling.
• Familiarity with model deployment and inference optimization (MLOps patterns).

Nice to have

• GPU-accelerated computing, distributed training systems, data versioning or experiment tracking tools.
• Docker/Kubernetes exposure.
• Contributions to open-source ML projects.