Machine Learning Engineer - Remote

Overview

Perennial Systems is looking for a skilled Machine Learning Engineer with hands-on experience deploying models on Google Cloud Platform (GCP) using Vertex AI. This role involves enabling real-time and batch model inferencing based on specific business requirements, with a strong focus on production-grade ML deployments.

In Short

• Deploy machine learning models on GCP using Vertex AI.
• Design and implement real-time and batch inference pipelines.
• Monitor model performance, detect drift, and manage lifecycle.
• Ensure adherence to model governance best practices and support ML-Ops workflows.
• Collaborate with cross-functional teams to support Credit Risk, Marketing, and Customer Service use cases.
• Develop scalable and maintainable code in Python and SQL.
• Work with diverse datasets and perform feature engineering.
• Build, train, and fine-tune advanced predictive models.
• Contribute to model deployment in the lending space.

Requirements

• Strong expertise in Python and SQL.
• Proficient with ML libraries and frameworks such as scikit-learn, pandas, NumPy, spaCy, CatBoost, etc.
• In-depth knowledge of GCP Vertex AI and ML pipeline orchestration.
• Experience with ML-Ops and model governance.
• Exposure to use cases in retail banking—Credit Risk, Marketing, and Customer Service.
• Experience working with structured and unstructured data.

Benefits

• Prior experience deploying models in the lending domain is a plus.
• Understanding of regulatory considerations in financial services is beneficial.