Software Engineer, Fraud

Software Engineer, Fraud 🚀 JOIN THE FUTURE OF COMMERCE WITH WHATNOT! Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re re-defining e-commerce by blending community, shopping, and entertainment into a community just for you. As a remote co-located team, we’re inspired by innovation and anchored in our values https://www.whatnot.com/careers. With hubs in the US, UK, Germany, Ireland, Poland, and Australia, we’re building the future of online marketplaces –together. From fashion, beauty, and electronics to collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone. And we’re just getting started! As one of the fastest growing marketplaces https://a16z.com/marketplace-100/, we’re looking for bold, forward-thinking problem solvers across all functional areas. Check out the latest Whatnot updates on our news https://blog.teamwhatnot.com/ and engineering https://medium.com/whatnot-engineering blogs and join us as we enable anyone to turn their passion into a business, and bring people together through commerce. 💻 ROLE The Fraud Experience team builds intelligent, real-time systems that safeguard Whatnot’s marketplace from malicious activity. We design, develop, and deploy end-to-end, ML-driven systems that proactively identify and mitigate fraud — blending 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. 👋 You Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Software Engineer in Fraud team, you should bring 4+ years of software development experience in high-growth environments, along 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 — you think critically about 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, reproduc ... (truncated, view full listing at source)