# Labelbox Forward Deployed Engineer (FDE) Interview Guide Aced (formerly Exponent) publishes a public search API over its indexed pages; the guide is at https://www.aced.io/agents/agent-access. Source: https://www.aced.io/guides/labelbox-forward-deployed-engineer-interview Source observed: 2026-11-04T21:21:22.057Z Last checked: 2026-11-04T21:21:22.057+00:00 Indexed: 2026-11-05T00:51:52.84+00:00 --- # Labelbox Forward Deployed Engineer (FDE) Interview Guide Updated a month ago by Labelbox candidates. **Guide sections:** [Expert guide](https://www.aced.io/guides/labelbox-forward-deployed-engineer-interview) · [Interview experiences (1)](https://www.aced.io/guides/labelbox-forward-deployed-engineer-interview/experiences) · [Questions](https://www.aced.io/guides/labelbox-forward-deployed-engineer-interview/questions) · [Resumes](https://www.aced.io/guides/labelbox-forward-deployed-engineer-interview/resumes) ## What this guide covers We provide a guide to the Labelbox forward deployed engineer interview, including the stages, what interviewers look for, preparation guidance, example questions, tips, and resources. Our [forward deployed engineering course](https://www.aced.io/courses/forward-deployed-engineering) is also available for broader preparation. The interview centers on designing a reinforcement learning dataset that can improve a research lab’s coding model. Candidates design an end-to-end data-curation plan as a take-home exercise, then present and defend it to a forward deployed engineer and the hiring manager. The process emphasizes data-quality rigor and delivery judgment as well as coding, and it screens for the role’s work intensity from the first call. Our guides are created from recent, real, first-hand insights shared by interviewers and candidates. If your experience differs, [tell us here](https://www.aced.io/questions/contribute). ## Labelbox forward deployed engineer interview process The process is built around a two-part technical assessment asking candidates to design a reinforcement learning dataset from scratch. The emphasis is on data-curation judgment: sourcing, annotating, and quality-checking a dataset that a research lab can train against. The full loop can move from a recruiter screen through a technical assessment, a behavioral round, and an onsite: 1. **Recruiter screen:** An introductory call covering your interest, background, and willingness to take on the role’s hours and intensity. 2. **Technical assessment, part one:** A take-home dataset-design plan and presentation built around a coding reinforcement learning dataset. 3. **Technical assessment, part two:** An in-person debrief in which you present a retrospective on your design to an FDE and the hiring manager. 4. **Peer and behavioral round:** A cultural conversation with peers and the manager focused on collaboration and delivery. 5. **Onsite loop:** Two to three sessions covering mission and values, a past-experience deep dive, and an informal chat. The FDE process changes often and is not tightly standardized, so timelines and communication between stages can vary. Some candidates describe a simpler loop of recruiter screen, hiring manager screen, case study, and onsite. Use this guide as a baseline and expect your own loop to differ. ## Recruiter screen The recruiter screen gauges your interest in the role and your willingness to take on its demands. Expect direct questions about long hours, weekend work, and being placed in front of top research labs early in your tenure. Work-ethic questions can appear at this stage as an early screen. The remainder of the guide is available to members. ## Membership and preparation resources Members receive the complete guide, all prep courses, practice tools, job referrals, and other preparation resources. [Become a member](https://www.aced.io/upgrade?src=guide) or [log in](https://www.aced.io/login?src=guide&returnPath=%2Fguides%2Flabelbox-forward-deployed-engineer-interview). We also invite people who recently interviewed for an FDE role to [share their interview experience and get compensated](https://call.insightscompany.io/c4e614c3-ce9b-401e-b2b8-b286b9ea6ea4/9f524116-caf4-4813-a205-cfe62a89fd92?src=guide). ## About Aced Aced, formerly Exponent, is a tech interview preparation platform. We provide free interview guides, insider tips, and courses. 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