ML Engineer
Indexed description
Preference will be given to candidates open to relocating to Manila
Your Future Tasks
- Own the end-to-end lifecycle of ML models: from EDA, feature generation, and hypothesis testing to production deployment and monitoring
- Collaborate with cross-functional teams - especially Collection and Product - to identify high-leverage modeling opportunities
- Evaluate model performance and business impact, and iterate for continuous improvement
- Explore and integrate new data sources (internal and external), identifying additional predictive signals
- Work with production systems to ensure models are scalable, observable, and maintainable
- 2+ years of experience as a Machine Learning Engineer or Data Scientist, ideally in fintech or fast-paced product environments
- Solid foundation in classical ML techniques and fluency in core libraries such as Pandas, Scikit-learn, NumPy, SciPy, Matplotlib, Seaborn, Statsmodels, XGBoost/LightGBM/CatBoost etc
- Strong proficiency in Python and SQL, experience with version control
- Strong sense of ownership and accountability
- Experience working with AWS (or other cloud environments) is a plus
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