Senior Machine Learning Engineer
About The Position
As a Senior Machine Learning Engineer on our Fraud Detection & Risk Assessment Data Science team, you will design, build, and deploy cutting-edge ML systems that protect millions of users and multiple product lines from evolving fraud and risk threats. You’ll work with complex, high-volume data streams to develop and deploy services that detect and prevent Fraud and enable real-time decisioning across our ecosystem. Collaborating closely with Product, Fraud Operations, Engineering and Data Science teams, you will translate business risk signals into robust machine learning pipelines—improving the accuracy, efficiency, and impact of our fraud detection systems. This role requires strong ownership across the ML lifecycle, from ideation to development to production systems, and a forward-looking mindset on applying Generative AI and agentic systems in fraud prevention.
Requirements
- PhD or Masters in Computer Science, Statistics, or a related field
- 5+ years of experience applying ML in production with measurable business impact.
- Expertise in machine learning algorithms and frameworks, with hands-on experience in training, tuning, deploying and monitoring models in production environments.
- Experience designing systems in adversarial or rapidly evolving environments (fraud, risk, etc.)
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with data pipeline tools and frameworks (e.g., Airflow, Spark, Kafka, or similar).
- 6+ months of hands-on experience building LLM/GenAI applications (RAG, agents, or decision-support systems).
- Excellent problem-solving, communication, and cross-functional collaboration skills.
- Bachelor's Degree or equivalent experience
Responsibilities
- Design, build, and deploy cutting-edge ML systems that protect millions of users and multiple product lines from evolving fraud and risk threats.
- Work with complex, high-volume data streams to develop and deploy services that detect and prevent Fraud and enable real-time decisioning across our ecosystem.
- Translate business risk signals into robust machine learning pipelines—improving the accuracy, efficiency, and impact of our fraud detection systems.
- Take strong ownership across the ML lifecycle, from ideation to development to production systems.
- Apply Generative AI and agentic systems in fraud prevention.
Benefits
- medical
- dental
- vision
- 401k plan
- discretionary vacation for exempt team members
- paid holidays
- paid sick leave
- annual bonus
- potential for restricted stock units
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
1,001-5,000 employees
