Software Engineer, Fraud

About Whatnot

Whatnot is the largest livestream shopping platform in North America and Europe, where users can buy, sell, and discover items they love. From trading cards to fashion and electronics, our sellers are building real businesses across hundreds of categories. We are pioneering live commerce at a scale never before seen in the West, operating without a pre-existing playbook. The people here are actively shaping the development of an entirely new industry.

As a remote co-located team, we are driven by our values and have hubs across the US, UK, Ireland, Poland, Germany, and Australia. We prioritize speed, user proximity, and high-impact work. Whatnot is one of the fastest-growing marketplaces and was recently named the #1 Best Startup Employer in America by Forbes. Explore our news and engineering blogs to learn more, and join us in enabling individuals to turn their passions into businesses and fostering connection through commerce.

The Role: Software Engineer, Fraud

The Fraud Experience team is dedicated to building intelligent, real-time systems that protect Whatnot’s marketplace from malicious activity. We design, develop, and deploy end-to-end, ML-driven systems that proactively identify and mitigate fraud, combining sophisticated real-time detection with transparent, user-centered enforcement.

What You'll Do

• Lead the full architecture of fraud detection, prevention, and intervention systems, spanning machine learning, backend, and client-side components.
• Build intelligent user graphs to model behavioral patterns, detect collusion networks, and uncover account connectivity at scale.
• Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent activity across users, payments, and marketplace interactions.
• Develop scalable data pipelines and real-time inference systems capable of supporting high-volume, low-latency ML workloads.
• Create human-in-the-loop systems that continuously refine detection accuracy and adapt to evolving adversarial tactics.
• Perform deep behavioral and adversarial data analysis to surface emerging fraud trends and drive continuous system improvement.
• Stay ahead of the curve by translating new insights into adaptive, production-ready systems that evolve as fast as our adversaries.

We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Los Angeles, New York, San Francisco, or Seattle hub.

Who You Are

Individuals who thrive at Whatnot are comfortable navigating ambiguity, have a bias toward action, and possess genuine curiosity for what they are building. They prioritize outcomes over individual credit and maintain a close connection to the product and its users. As our next Software Engineer, Fraud, you should bring 4+ years of software development experience in high-growth environments, coupled with a strong bias toward action and impact.

What You’ll Bring

• Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, Economics, or a related technical field.
• 4+ years of software engineering experience building systems for consumer-scale traffic and reliability.
• 1+ years writing production-grade Python code and working with ML libraries (e.g., PyTorch, LightGBM).
• 1+ years of experience in machine learning or fraud prevention domains.
• Deep business intuition and a data-driven mindset, critically assessing how abuse prevention systems affect growth and user experience.
• Fluency with data tooling, including data warehouses (e.g., Snowflake) and transformation frameworks (e.g., dbt, Dagster).
• Strong communication skills and the ability to lead initiatives across product areas, collaborating closely with leadership, data science, and product teams.
• Experience working in a remote-first environment and producing well-tested, reproducible work.

What Sets You Apart

• You’re impact-obsessed, relentlessly focusing on delivering value for users and simplifying wherever possible, moving fast without sacrificing quality.
• You’re entrepreneurial and relentless, prioritizing effectively, tackling hard problems with curiosity, and going above and beyond to make things happen.
• You have a growth mindset and love digging into ambiguous user problems, crafting data-driven solutions, and shipping improvements quickly.
• Hands-on machine learning or data science experience in production environments.

Benefits

• Generous Holiday and Time off Policy.
• Health Insurance options including Medical, Dental, Vision.
• Work From Home Support: Home office setup allowance, Monthly allowance for cell phone and internet.
• Care benefits: Monthly allowance for wellness, Annual allowance towards Childcare, Lifetime benefit for family planning, such as adoption or fertility expenses.
• Retirement: 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally.
• Monthly allowance to "dogfood" the app: All Whatnauts are expected to develop a deep understanding of our product by using Whatnot as both a buyer and a seller.
• Parental Leave: 16 weeks of paid parental leave + one month gradual return to work (company leave allowances run concurrently with country leave requirements which take precedence).

Equal Opportunity Employer

Whatnot is proud to be an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

Compensation Range

The compensation range for this position is $170,000 - $230,000 USD.

Key skills/competency

• Fraud Detection
• Machine Learning
• Real-time Systems
• Python Programming
• Data Pipelines
• System Architecture
• Adversarial Analysis
• Risk Mitigation
• SQL/Data Warehousing
• Consumer-scale Traffic