Software Engineer focused on building AI development tools and infrastructure to enhance engineering productivity and enable autonomous agent capabilities within the company's codebase and processes. This role involves designing sandboxed environments, orchestration systems, and AI-aware infrastructure, acting as a primary interface between the Developer Tools team and the AI Tooling Working Group.

Software Engineer to build and own AI tooling for the engineering organization, focusing on AI coding agents and assistants. This role involves building infrastructure, workflows, and orchestration systems for AI agents to operate within the company's codebase and processes, enabling both engineers and non-engineers to leverage AI tools effectively. The role requires strong software engineering skills and familiarity with current AI development tools.

Machine Learning Engineer role focused on building and deploying ML models for personalized navigation, search, and recommendations on a livestream shopping platform. The role involves end-to-end ML project lifecycle, from data to production, and requires experience in applied ML fields like search and recommendations.

Machine Learning Engineer focused on designing, training, and deploying ML models and systems for fraud detection and prevention in a high-volume marketplace. This includes building user graphs, real-time inference systems, and monitoring, with a strong emphasis on end-to-end ownership and integrating ML into fraud orchestration.

Machine Learning Engineer on the Discovery Content and Navigation team, focusing on building and deploying ML models for personalized navigation, search, and recommendations in a high-growth consumer marketplace. The role involves end-to-end project ownership, from data collection to production deployment and experimentation, with a strong emphasis on applied ML methods for consumer-scale data.

Software Engineer role focused on building and scaling the Discovery Platform, including recommendation systems, feed, browse, and search functionalities. This involves integrating retrieval, machine learning ranking, real-time processing, and content understanding to create a personalized discovery experience for a live shopping marketplace.

Software Engineer role focused on building and deploying ML-driven systems for fraud detection, prevention, and intervention in a real-time, high-volume marketplace. Responsibilities include developing intelligent user graphs, training and deploying traditional ML and LLM models, creating scalable data pipelines, and implementing human-in-the-loop systems to adapt to evolving fraud tactics.

Software Engineer for Whatnot's Trust & Risk team, focusing on building and iterating on production algorithms and infrastructures to mitigate systemic risks, safeguard users, and prevent abuse. The role involves designing event-driven pipelines for real-time threat response, balancing risk with user experience, and collaborating across teams to continuously evolve defenses against emerging abuse patterns. Experience with machine learning, behavioral analysis, and data warehouses is preferred.

Software Engineer role focused on building systems for trust, risk, fraud, and integrity within a consumer marketplace. The role involves designing and developing production algorithms and infrastructures to mitigate systemic risks, protect users, and prevent abuse. It requires experience in event-driven pipelines, detection frameworks, and a data-driven mindset, with a preference for experience in Trust and Risk or Fraud domains. Explicit data science or machine learning experience is a plus.

Software Engineer role focused on building and deploying ML-driven systems for fraud detection, prevention, and intervention in a livestream shopping marketplace. Responsibilities include developing intelligent user graphs, training and deploying traditional ML and LLM models, creating scalable data pipelines, real-time inference systems, and human-in-the-loop systems for continuous refinement. The role emphasizes analyzing behavioral and adversarial data to identify emerging fraud trends and evolving systems to combat them.

Fullstack Engineer for Whatnot's Trust and Risk team, focusing on building systems for policy enforcement, dispute resolution, and intelligent detection/prevention of abuse using ML and behavioral analysis. The role involves developing features to ensure a safe and trustworthy marketplace.

Fullstack Engineer role focused on seller growth, involving building systems for fraud detection, identity verification, seller enrichment pipelines, and A/B testing. The role also involves creating scalable data pipelines and growth systems. While not directly building core AI models, the role leverages and builds systems that incorporate predictive models and signals for seller routing and risk assessment, indicating an AI-adjacent function within a consumer marketplace.

Software Engineer, Horizontal Ops at Whatnot, a livestream shopping platform. The role involves building internal operations tooling, including a workflow engine for intelligent, automated resolutions and AI-powered automations to help ops teams work faster and more reliably. Focus on backend systems, scaling infrastructure, and translating business problems into technical solutions.

Software Engineer, CX at Whatnot, a livestream shopping platform. This role focuses on building a world-class Customer Support platform, including user-facing experiences, scaling internal infrastructure, and designing intelligent AI-powered automations to handle a high volume of customer issues. The engineer will lead solutions end-to-end, translating business problems into technical solutions and driving delivery.

Software Engineer, CX at Whatnot, a livestream shopping platform. This role focuses on building a world-class Customer Support platform, including user-facing experiences, scaling internal infrastructure, and designing AI-powered automations to handle customer issues. The engineer will lead solutions end-to-end, translating business problems into technical solutions and driving delivery.

Software Engineer, Horizontal Ops at Whatnot, focusing on building internal operations tooling and AI-powered automations for customer support and trust & safety workflows. The role involves developing a workflow engine for intelligent, automated resolutions at scale.

Data Scientist focused on risk and fraud detection for a livestream shopping platform. The role involves translating data into actionable recommendations, defining KPIs, analyzing existing methods, partnering with ML engineers to develop anti-fraud practices, designing and evaluating experiments, developing causal inference frameworks, building data products, and collaborating cross-functionally to shape fraud strategy. Requires advanced SQL, Python/R, A/B testing, and causal inference experience.

Data Scientist focused on risk and fraud detection for a livestream shopping platform. The role involves translating data into actionable recommendations, defining KPIs, analyzing existing methods, partnering with ML engineers to develop anti-fraud practices, designing and evaluating experiments, developing causal inference frameworks, building data products, and collaborating cross-functionally to shape fraud strategy. Requires advanced SQL, Python/R, A/B testing, and causal inference experience.

Lead Backend Engineer for the Customer Experience Platform team, responsible for building a world-class Customer Support platform. This includes developing user-facing experiences, scaling infrastructure, and designing intelligent AI-powered automations to handle high volumes of customer issues. The role involves end-to-end solution ownership, translating business problems into technical solutions, and driving delivery and experimentation.

Software Engineer on the Seller Growth Platform pod responsible for designing and building systems that sit at the heart of the new seller funnel. This includes developing and scaling systems for identity verification, fraud detection, and automated trust/risk reviews, as well as powering accurate seller identification through enrichment data, signals, and predictive LTV models. The role also involves creating scalable infrastructure like reusable trust and reputation systems and modular fraud prevention frameworks, and driving long-term seller success by enabling better bucketing of sellers by value and risk profile.