Machine Learning Engineer

ML Engineer

On-site 5 days per week (CBD)

Base plus discretionary bonus

Private HFT Firm

Sydney or Hong Kong

About the Firm

A well-capitalised, privately held high-frequency trading firm operating across APAC markets. The team is intentionally small, consisting of highly capable individuals who value autonomy, ownership, and execution over process and hierarchy.

The Role

This is a hands-on ML Engineering role embedded directly within the trading research team. You will be responsible for designing, building, and deploying large-scale machine learning systems that support live trading strategies.

This is not a management position. You will work closely with quant researchers and traders, translating research into robust, production-grade systems. There is no separate ML team. You will own the machine learning function end to end.

Key Responsibilities

• Own the full machine learning lifecycle, including data ingestion, feature engineering, model training, deployment, and monitoring
• Build and maintain scalable, high-quality data pipelines
• Deploy, optimise, and support large-scale models in a latency-sensitive production environment
• Partner directly with traders and quantitative researchers to productionise research and trading strategies
• Continuously improve the firm's machine learning infrastructure, tooling, and workflows

Requirements

• Strong machine learning engineering experience with a proven track record of building and maintaining production systems
• Expert-level Python skills; experience with C++ is advantageous
• Experience designing and operating large-scale data pipelines and model deployment infrastructure
• Background in high-frequency trading, algorithmic trading, or quantitative research is highly regarded
• Experience building ML infrastructure within leading technology companies will be viewed favourably
• Strong academic pedigree and a desire to take ownership in a high-performance environment
• Based in APAC or willing to relocate

What's on Offer

• Full ownership of machine learning within a highly successful trading firm
• Direct impact on trading performance and business outcomes
• Minimal bureaucracy and fast decision-making
• Highly competitive compensation aligned with the calibre of candidate being sought
• Small, elite team working on complex and intellectually challenging problems