Requirements:

Bachelor’s degree or equivalent practical experience.
1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
1 year of experience with data structures or algorithms.

Nice to Haves:

Master's degree in Computer Science, Machine Learning, a related field, or equivalent practical experience.
2 years of experience developing and deploying machine learning models, especially deep learning or natural language processing techniques.
2 years of experience with large-scale distributed systems in the context of machine learning infrastructure or applications.
Experience in adversarial space, fraud detection, or other anti-abuse domains.
Familiarity with TensorFlow or similar frameworks.

Design, build, optimize, and operate the Machine Learning (ML) ecosystem that powers transformer-based account activity models.
Implement ML pipelines for seamless experimentation, feature engineering, model training, validation, and deployment, accelerating the time-to-production for new threat detection models.
Design and implement model metrics and benchmarks aiding in explainability of model behavior.
Analyze models drift and identify opportunities for refinement, ensuring sustained models accuracy and effectiveness.
Collaborate closely with our partners, including Trust and Safety to ensure a seamless adoption in our daily threats fighting operations.

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English proficiency is a requirement for all roles.
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