Software Engineer (Machine Learning)

TL;DR

Software Engineer (Machine Learning): Architecting and building mission-critical infrastructure for ML workflows and model iteration velocity with an accent on designing training pipelines, automated data workflows, and integration tooling. Focus on scaling research demand, large-scale data collection, and streamlining experiment lifecycles.

Location: Work 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 that streamline experiment lifecycles and reduce turnaround time.
• Collaborate closely 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 working 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).
• Must be able to work on-site in Hong Kong.

Nice to have

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