ML Engineer

Salmon Group; Manila; On-site; PHP 390,600 - 781,200; Full time

Job summary

Salmon Group is seeking a Machine Learning Engineer to join our Manila team and drive the development of innovative ML solutions. This role enables collaboration with multiple departments, focusing on impactful projects in credit scoring, collection, antifraud, and sales.

Applicants should have 2+ years of experience, proficiency in Python and SQL, and a solid foundation in classical ML techniques. Experience with AWS is a plus.

Qualifications

• 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 and Scikit-learn.
• Strong proficiency in Python and SQL, experience with version control.

Responsibilities

• Own the end-to-end lifecycle of ML models from EDA to production deployment.
• Collaborate with cross-functional teams to identify modeling opportunities.
• Evaluate model performance and iterate for continuous improvement.
• Explore and integrate new data sources and predictive signals.
• Work with production systems to ensure model scalability and observability.

Skills

Machine Learning techniques

Pandas

Scikit-learn

Python

SQL

AWS

Tools

NumPy

SciPy

Matplotlib

Seaborn

Statsmodels

XGBoost

LightGBM

CatBoost

Job description

We’re looking for a curious and impact‑driven Machine Learning Engineer to join our team and accelerate the development of robust, high‑performing ML solutions across key business areas — including credit scoring, collection, antifraud, sales and other.

This role combines hands‑on development with strategic input, offering a chance to work on high‑stakes, high‑visibility projects from day one, collaborating with multiple departments and stakeholders to drive measurable business impact through better models.

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

What we expect from candidate:

• 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