Software Engineer, Fraud at whatnot

This role is ideal for a mid-to-senior backend or machine learning engineer with at least 4 years of experience who thrives in high-growth, fast-paced environme

Work type: onsite

Location: San Francisco, CA | Los Angeles, CA | Seattle, WA | New York, NY

Salary: $170,000 – $230,000/yr

Type: Full-time

Summary

This role is ideal for a mid-to-senior backend or machine learning engineer with at least 4 years of experience who thrives in high-growth, fast-paced environments. You should have a solid foundation in Python and a proven track record of building production-grade systems for consumer-scale traffic. The team is looking for a "builder" mindset—someone who can bridge the gap between complex data science (ML/LLMs) and robust backend architecture to stop bad actors in real-time. The compensation is highly competitive ($170k - $230k) and comes with a robust benefits package, including a 4% 401k match, 16 weeks of parental leave, and unique perks like a "dogfooding" budget to shop on the platform. While the team values flexibility, this is a **remote co-located** model; you must live within commuting distance of their hubs in San Francisco, Los Angeles, Seattle, or New York for occasional in-person collaboration. **You might be a good fit if you...** * Have 1+ years of experience specifically in fraud prevention, trust and safety, or risk engineering. * Are proficient with Python and ML libraries like PyTorch or LightGBM, and familiar with data tools like Snowflake or dbt. * Enjoy "adversarial thinking"—anticipating how hackers or scammers will try to bypass your systems. * Prefer a "low ego, high impact" culture where you ship code quickly to solve ambiguous problems.

Job Description

## 🚀 Join the Future of Commerce with Whatnot!

Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.

As a remote co-located team, we're inspired by our [values](https://www.whatnot.com/careers) and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.

We're one of the [fastest growing marketplaces](https://a16z.com/marketplace-100/) and were recently named the [#1 Best Startup Employer in America](http://google.com/search?q=%231+forbes+startup+employer&oq=%231+forbes+startup+employer&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIGCAEQRRg9MgYIAhBFGD0yBggDEEUYQDIGCAQQRRhAMgYIBRBFGEDSAQg1NzM0ajBqMagCALACAA&sourceid=chrome&ie=UTF-8) by Forbes. Check out the latest Whatnot updates on our [news](https://blog.teamwhatnot.com/) and [engineering blogs](https://medium.com/whatnot-engineering) 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.

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, reproducible work.

• 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.

• 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.

## 💛 EOE

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we 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.

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