Senior Software Engineer - Fraud

Roblox Roblox · Consumer · San Mateo, CA · Software Engineering

Senior Software Engineer focused on developing anti-fraud and abuse solutions for Roblox's virtual marketplace. This role involves building backend services, fraud platform components, and pipelines, leveraging data-driven approaches and machine learning to detect and prevent fraud. The engineer will also contribute to the technical roadmap and risk defense strategy, bridging communication between backend engineers and data scientists/ML engineers.

What you'd actually do

  1. Develop backend services, fraud platform components, and pipelines to implement product logic, encourage eng efficiency, and produce features for ML models.
  2. Be a Tech Lead that contributes to our Technical Roadmap and Risk Defense strategy.
  3. Up-level our data mining and data-driven approaches.
  4. Occasionally perform data analysis to understand our Fraud & Abuse domain.
  5. Occasionally bridge communication between generalist backend engineers, and data scientists and ML engineers.

Skills

Required

  • 4+ years of professional experience working with scalable, distributed systems
  • Strong experience in large-scale, data-driven architecture, API design, data modeling, and SQL / NoSQL data storage.
  • Experience in risk prevention, machine learning, or analytical work.
  • Passion for delivering products end-to-end, from ideation through implementation and A/B testing, while being empathetic with cross-functional stakeholders.
  • Strong ownership with proactive, candid communication, and an ability to handle high complexity
  • Bachelor's Degree or above in Computer Science or another quantitative field

Nice to have

  • Help recruit future talent for the team

What the JD emphasized

  • critical for the well-being of our community and to the future of our company
  • develop both classical and novel approaches to detect and prevent this bad behavior
  • risk prevention, machine learning, or analytical work

Other signals

  • develop anti-fraud and abuse solutions
  • data-driven environment developing both classical and novel approaches to detect and prevent this bad behavior
  • develop backend services, fraud platform components, and pipelines to implement product logic, encourage eng efficiency, and produce features for ML models