Machine Learning Engineer

TL;DR

Machine Learning Engineer (ML/MLOps): Build and operate production systems that power fraud detection products, with an accent on training, evaluation, inference, and reliable deployment at scale. Focus on production engineering practices, monitoring and troubleshooting ML systems, and productionalizing models into scalable applications.

Location: Cary, North Carolina

Company

hirify.global builds digital banking and lending solutions for financial institutions and fintechs.

What you will do

• Build and maintain systems and pipelines for ML training, evaluation, and inference.
• Deploy ML models into production and ensure they run reliably at scale.
• Write clean, maintainable, well-tested production code and follow production engineering best practices.
• Monitor and troubleshoot production ML systems, including data pipelines and model performance.
• Collaborate with data scientists and engineers to productionalize models and integrate them into scalable applications.
• Improve reliability, scalability, and performance of ML systems over time; enhance ML tooling and infrastructure.

Requirements

• 2+ years of related experience (or advanced degree / equivalent experience) and a Bachelor’s degree in a relevant field.
• Proficiency in Python.
• Experience writing clean, maintainable code and using version control (e.g., Git).
• Experience with machine learning and common frameworks (PyTorch, TensorFlow, scikit-learn).
• Fluent written and oral communication in English.
• Authorization to work for any employer in the U.S.; unable to sponsor or take over sponsorship of an employment visa.

Culture & Benefits

• Hybrid work opportunities.
• Flexible time off.
• Health and wellness benefits, including competitive health insurance and generous paid parental leave for eligible new parents.
• Career development and mentoring programs.
• Community volunteering and company philanthropy programs.
• Employee peer recognition programs.

Hiring process

• Not specified in the posting.