Software Engineer, Fraud

Whatnot•San Francisco, CA

10h•Hybrid

About The Position

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 . With hubs in the US, UK, Germany, Ireland, and Poland, 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 , we’re looking for bold, forward-thinking problem solvers across all functional areas. 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. 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.

Requirements

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, reproducible work.

Nice To Haves

You’re impact-obsessed — you focus relentlessly on delivering value for users and simplify wherever possible, moving fast without sacrificing quality.
You’re entrepreneurial and relentless — you prioritize effectively, tackle hard problems with curiosity, and go 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.

Responsibilities

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.

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. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
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.