Job Information
Meta Software Engineer, Machine Learning (Tel Aviv) in Tel Aviv, Israel
Summary:
The FI Advertiser Risk team is part of the Meta FinTech (MFT) engineering teams dealing with Risk, Compliance and Care (AKA Financial Integrity). The team is a part of the Risk pillar which leads risk mitigation throughout the customer and business journey.The team's focus is the Ads Fraud Risk domain, and its goal is to mitigate fraud and reduce friction for advertisers. We work on boosting our fraud detection with additional policies, algorithms and ML solutions and improving detection of scaled fraud attacks.We are building our next generation Fraud detection system as part of FI's Risk-as-a-Service effort.Our Tech:We are using a variety of ML and stats models and algorithms, from classic supervised learning, to anomaly detection, unsupervised learning and semi supervised learning, to detect and mitigate ongoing fraud campaigns.In our solutions we are using Graph Neural Networks, Ensembles, Boosting, Regression models, Time Series data, Causal Inference and more.
Required Skills:
Software Engineer, Machine Learning (Tel Aviv) Responsibilities:
Leading projects or small teams of people to help them unblock, advocating for ML excellence.
Develop highly scalable classifiers and tools leveraging machine learning, data, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmaps
Code deliverables in tandem with the engineering team
Minimum Qualifications:
Minimum Qualifications:
Experience with developing machine learning models at scale from inception to business impact
Experience of ML for Fraud detection and/or solving other integrity problems
Experience in software engineering or a relevant field. 3+ years of experience if you have a PhD
Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or a related technical field.
Knowledge developing and debugging
Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Preferred Qualifications:
Preferred Qualifications:
Masters degree or PhD in Computer Science or a related technical field
Exposure to architectural patterns of large scale software applications
Python and PHP/Hack experience
Industry: Internet