Machine Learning Engineer

Location: Shanghai, China; hybrid working opportunities are available.

Company

hirify.global is a quantitative trading firm developing electronic trading infrastructure, research platforms, and business support systems for independent trading teams.

What you will do

• Architect and develop a scalable, reliable, observable, and reproducible machine learning research platform.
• Build infrastructure for large-scale experimentation, model training, and simulation across on-premises HPC and multi-cloud environments.
• Design and optimize distributed, GPU-accelerated training pipelines and improve compute efficiency, resource scheduling, and workload isolation.
• Develop tools for feature engineering, dataset generation, large-scale backtesting, experiment management, model versioning, artifact tracking, and data lineage.
• Partner with quantitative researchers to translate research workflows into robust platform capabilities.
• Contribute to architectural decisions and maintain high engineering standards while delivering features and fixes on tight timelines.

Requirements

• At least 2 years of experience designing and building large-scale distributed systems.
• Strong Python programming skills and a focus on clean, maintainable, high-performance code.
• Experience operating applications on Linux-based HPC clusters and/or cloud platforms.
• Understanding of distributed computing, parallel processing, and resource management.
• Experience with GPU-based workloads and modern machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience optimizing data pipelines and working with large-scale structured and unstructured datasets, plus strong troubleshooting and communication skills.

Nice to have

• Experience building internal machine learning platforms or research tooling at scale.
• Familiarity with experiment tracking, workflow orchestration, and model lifecycle management.
• Experience with Docker and Kubernetes.
• Exposure to quantitative finance, simulation systems, or latency- and performance-sensitive domains.

Culture & Benefits

• Hybrid working opportunities and generous paid time off.
• Savings plans and financial wellness tools available in each region.
• Free breakfast, lunch, and snacks daily, plus in-office wellness experiences and selected wellness expense reimbursement.
• Company-sponsored sports teams, fitness events, volunteer opportunities, charitable giving, and social events.
• Workshops and continuous learning opportunities in a collaborative workplace with minimal hierarchy.