Machine Learning Engineer

Machine Learning Engineer (MLE)

Background on what ING is about:

ING Hubs Philippines (ING Hubs PH) is an international part of the ING organization delivering services to many Business Units across the world for both Wholesale Banking and Retail Banking activities. Working for ING Hubs PH means working with the most diverse workforce and where no challenge is the same.

At ING our purpose is to empower people to stay a step ahead in life and business. We believe that sustainable progress is driven by people with the imagination and determination to make a better future for themselves and those around them.

ING is changing what banking is. For you, that means plenty of opportunities for personal growth in a continuously evolving environment. If this is the environment you thrive in, then apply and join us in changing the future of banking!

Job Overview

We are seeking a passionate professional eager to work with cutting-edge technologies in the dynamic field of Machine Learning Engineering. This role offers the opportunity to innovate, build, and deploy advanced solutions that leverage the latest advancements in AI and ML, driving impactful outcomes across our organization.

Key Responsibilities

• Experience in creating, training, evaluating, and fine-tuning AI models (including working with vectorizers, embeddings, etc.).
• Understanding of MLOps architecture and methodologies (e.g., CI/CD or pipeline automation).
• Applied software engineering best practices, including version control, testing, documentation, and code review.
• Data Collection and Preparation: Gather, clean, and preprocess large datasets for training and testing and ensure data quality, representation, and compliance with governance standards.
• Staying updated on emerging ML technologies, frameworks, and best practices.
• Collaborative: Can work closely with data scientists, software engineers, and product teams.

Key Capabilities/Experience

• Hands-on development experience with Python.
• Experience designing distributed software using cloud-based managed services (preferably GCP or Azure).
• Experience implementing deployment and provisioning automation tools such as Docker, Kubernetes, OpenShift, and CI/CD pipelines.
• Familiarity with machine learning technologies and frameworks, such as Scikit-learn, MLflow, TensorFlow (including those available on GCP).
• Experience building data pipelines, including ETL processes and data processing frameworks like PySpark.
• Proficiency in data manipulation and transformation using tools such as SQL.

Minimum Qualifications:

• Hard skills: Experience in using Python, GCP or Azure, Scikit-learn, MLFlow, Openshift or Kubernetes, ETL development using SQL or Pyspark, worked with CICD pipelines.

• Soft Skills: Communication skills, Collaborative attitude, Socially Aware/Intelligent