Join Our Team as a Machine Learning Engineer in Financial Integrity Risk at Meta

At Meta, we are at the forefront of transforming financial technologies through our dedicated Financial Integrity (FI) Risk team within the Meta FinTech (MFT) sector. This key team focuses on Risk, Compliance, and Care, playing a crucial role in detecting and preventing financial discrepancies such as fraud across both customer and business interactions.

About Our Technology

Our team utilizes a dynamic mix of machine learning (ML) and statistical models to combat fraudulent activities effectively. We implement advanced techniques including supervised, anomaly detection, unsupervised, and semi-supervised learning. Our solutions incorporate cutting-edge technologies such as Graph Neural Networks, Ensembles, Boosting, Regression Models, Time Series, and Causal Inference to stay ahead of ongoing fraud campaigns.

Role Responsibilities

As a Machine Learning Engineer in Financial Integrity Risk, you will:

• Lead the vision and objectives for the ML division, focusing on project impact, ML system architecture, and overall excellence.
• Manage the full development cycle from concept to deployment, across various tech stacks.
• Develop, test, and implement ML models using techniques like supervised, unsupervised, and deep learning.
• Collaborate with software engineers to integrate ML models into broader applications and systems.
• Work alongside data scientists to select the best ML algorithms and methods for specific tasks.

Minimum Qualifications

Our ideal candidate will have:

• Experience in developing scalable machine learning models from inception to significant business impact.
• Strong foundations in machine learning, classification, recommendation systems, pattern recognition, data mining, or artificial intelligence.
• Proficient communication skills with effective team collaboration abilities.
• Experience coding and debugging in PHP/Python.
• A Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications

We prefer candidates who have:

• Exposure to large-scale A/B testing systems, particularly within financial institutions or cybersecurity firms.
• A Master's degree in Mathematics, Statistics, or a related field, or equivalent practical experience.
• Experience with Python and PHP/Hack.

About Meta

Since launching in 2004, Meta has revolutionized how people connect. Today, we are pioneering new pathways by focusing on immersive technologies such as augmented and virtual reality, driving social interaction beyond traditional digital means. At Meta, you will have the opportunity to grow your career by developing technologies that reach beyond the known limits and help shape future social platforms.

Meta deeply values diversity and inclusivity and is committed to providing reasonable accommodations in our recruitment processes for individuals with disabilities, long-term conditions, mental health issues, religious beliefs, neurodiversity, or pregnancy-related needs. Should you require accommodations, please contact [email protected].

Ready to take on the challenge of protecting financial integrity with cutting-edge technology? Apply now to become a Machine Learning Engineer in Financial Integrity Risk at Meta and help shape the future of secure, innovative financial technologies.