Software Engineer - USDS

About the Team

We are seeking a talented Software Engineer to join our embedded Trust and Safety team, focusing on proactive risk detection. You'll be a key contributor to our mission, developing impactful solutions that address high-harm, high-risk issues where traditional detection methods may fall short.



As a Software Engineer on the Risk and Response Detection and Automation team, you will contribute to the full lifecycle of our tools, from early concepts to production deployment. You'll play a vital role in our Detection Engineering program, helping to build and scale systems that identify high-harm content and behavioral leakage on the platform. This involves collaborating closely with cross-functional Trust and Safety and Security teams on threat initiatives, refining tools to minimize false positives, and developing automation technologies to streamline critical processes. You'll have opportunities to build a range of solutions, from intuitive threat-intelligence platforms and workflow engines to knowledge discovery aids powered by Large Language Models (LLMs) and Retrieval Augmented Generation (RAG).



This role may be exposed to harmful content as part of their core day-to-day functions, as well as in project work; in response to escalation requests; or by chance.



Some content viewed may violate our community guidelines which include but are not limited to bullying; hate speech; child abuse; sexual assault; torture; bestiality; self-harm; suicide; and murder.



In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.



Responsibilities

- Build and implement compelling and usable tools with technologies like React, Python, and Golang to improve consistency and efficiency across US Trust & Safety.

- Collaborate directly with users to inform, refine, and validate concepts, translating user needs into robust and scalable features from MVP to production.

- Develop and deploy lightweight models in Python and SQL for our Detection Engineering program, helping to catch high-harm content and behavioral leakage at scale.

- Contribute to the exploration and application of AI/LLM technologies to enhance our proactive detection capabilities and reduce the technical lift of current bespoke systems.

- Participate actively in team events, including hackathons, monthly product demos, and quarterly on-sites.

- Analyze metrics and derive insights to continuously raise the effectiveness of our tooling and detection solutions.