Whatnot has 33 active AI-related job listings, with a significant focus on agents, which accounts for 64% of their open roles. The majority of these positions are within the Engineering function, and all hiring is currently concentrated in the United States. Their technical needs are reflected in frequent tags such as model_serving, inference_infra, and agent_orchestration. In the last 30 days, Whatnot posted 2 new AI roles, representing a 78% decrease compared to the previous 30-day period.
Currently tracking 20 active AI roles, down 31% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $245k–$345k (avg $296k).
Whatnot currently has 9 active AI-related roles in our index. The most common open titles are: AI Tooling Engineer, Data Scientist, Risk & Fraud, Engineering Manager, Feed, Machine Learning Engineer, Growth, Software Engineer, AI Dev Tools. Most positions are in Engineering.
Whatnot's active AI hiring is concentrated in: agents (89%), application (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Whatnot is hiring AI talent in: United States (9 roles).
Job postings at Whatnot most frequently reference: agent orchestration, recommender systems, search ranking, model serving, rag.
In the past 30 days, Whatnot has posted 2 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| AI Tooling Engineer Senior AI Engineer to build internal tools, prototypes, and business workflows that put AI into the hands of every team at Whatnot. This role involves owning ambiguous, cross-org bets end-to-end, shipping working software fast, hardening what works, and scaling how Whatnot gets value out of AI. The engineer will define reusable patterns and shared infrastructure, integrate AI tools with internal systems, and stay ahead of the AI landscape. This is a builder role focused on applying off-the-shelf AI, not model training or research. | Agent | 8 |
| Machine Learning Engineer, Growth Machine Learning Engineer focused on driving top-of-funnel growth and first-time buyer success for a livestream shopping platform. This role will build and own ML models for personalization in onboarding and user targeting, impacting buyer growth and first-time user conversion. | Ship | 7 |
| Software Engineer, AI Dev Tools 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. | Agent | 7 |
| Software Engineer, Trust & Risk 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. | Agent | 7 |
| Software Engineer, Fraud 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. | AgentData | 7 |