Senior Software Engineer - Fraud

Economy Fraud Engineer

Defend Roblox from all types of fraud, including theft, scams, money laundering, and payment fraud.

• Develop anti-fraud and abuse solutions for web, mobile, and 3D environments.
• Work in a data-driven environment developing both classical and novel approaches to detect and prevent bad behavior.
• Collaborate with cross-functional teams to deliver products end-to-end, from ideation through implementation and A/B testing.
• Contribute to the Technical Roadmap and Risk Defense strategy.
• Up-level data mining and data-driven approaches.
• Occasionally perform data analysis to understand the Fraud & Abuse domain.
• Occasionally bridge communication between generalist backend engineers, data scientists, and ML engineers.
• Help recruit future talent for the team.

Requirements

• 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.

Benefits

• Annual Salary Range: $196,750—$243,290 USD
• Eligible for equity compensation and benefits as described on this page.

Pay

• The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range.

Qualifications

• Experience in developing backend services, fraud platform components, and pipelines to implement product logic, encourage engineering efficiency, and produce features for ML models.
• Ability to occasionally perform data analysis to understand the Fraud & Abuse domain.
• Ability to occasionally bridge communication between generalist backend engineers, data scientists, and ML engineers.
• Ability to help recruit future talent for the team.