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 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.