Machine Learning Engineer

We are seeking a Machine Learning Engineer to join a high-impact, data-driven team focused on developing and deploying machine learning models that drive investment research and trading strategies. This role sits at the intersection of applied machine learning, large-scale data processing, and quantitative modeling.

Responsibilities

Design, implement, and optimize scalable machine learning pipelines to process and extract insights from massive, high-frequency datasets.
Collaborate closely with quantitative researchers and engineers to integrate ML models into production trading systems.
Build robust tools for feature engineering, data transformation, and model evaluation tailored to financial time series and alternative datasets.
Perform rigorous analysis to validate models and detect potential edge cases or data issues in a fast-paced, high-stakes environment.
Leverage modern ML techniques (e.g., supervised/unsupervised learning, ensemble methods, online learning) to support predictive modeling and alpha generation.

Key Qualifications

2+ years of hands-on experience in applied machine learning, preferably in a production-oriented or research-heavy setting.
Strong background in mathematics and statistics, with a focus on areas such as optimization, probability theory, and statistical inference.
Expert-level programming skills in Python, including popular ML and data libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow).
Proficiency in working in Linux-based environments, with solid experience handling large-scale distributed data and compute workflows.
Working knowledge of C++ is a plus, especially for interfacing with performance-critical systems.
Experience with large datasets, including data cleaning, transformation, and feature extraction at scale (e.g., billions of rows, TB-level data).

Bonus Skills

Exposure to high-frequency or low-latency systems and/or time-series modeling.
Familiarity with version control, CI/CD workflows, and modern software engineering best practices.
Interest or experience in financial markets, algorithmic trading, or quantitative investing.

Ideal Candidate Profile

A creative and curious mindset with the ability to translate abstract problems into practical ML solutions.
Strong communication skills and a team-oriented approach to working with researchers and engineers.
Proven track record of delivering production-quality ML systems in a dynamic, data-intensive environment.

NJF Global Holdings Ltd

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Machine Learning Engineer