Lead, Product Content Engineering

Product Content Engineering is a horizontal function supporting initiatives across Instagram and Meta AI, and is seeking a content engineer to lead media generation evaluations. We partner closely with product, research and modeling teams to set standards of quality and define what “good” looks like for generative image and video experiences.

This position is focused on model training for image and video generation capabilities. You will own the human evaluation layer that tells our models what quality means, designing the rubrics, running the eval rounds, and turning subjective creative judgment into reproducible, measurable signals that directly shapes model behavior and launch decisions.

The ideal candidate has built video and image evaluation rubrics from scratch and has hands-on video production expertise — they can articulate why a generated clip fails on motion coherence, lighting continuity, subject consistency, pacing, framing or audio sync, and can write that judgment down so that dozens of raters apply it the same way. They are fluent in text-to-video, image-to-video and video-to-video generation, and in the failure modes specific to each.

You will operate as the quality authority across multiple modeling work streams: setting the taxonomy, arbitrating disagreement, calibrating rater pools, and translating eval results into clear guidance for researchers and product leaders. You will also drive where human evaluation should give way to automated or LLM-as-a-judge measurement, and prove out that transition with data.

Lead, Product Content Engineering Responsibilities:

Own the evaluation rubrics for image and video generation models, define the quality dimensions, scales and decision rules, and maintain them as models and capabilities evolve.

Design and run human eval rounds that produce training and fine-tuning signal, including prompt set construction, golden sets and side-by-side model comparisons.

Set and defend the launch quality bar for generative media features, and make clear go / no-go quality recommendations.

Calibrate and manage rater pools and vendor teams monitor inter-rater reliability and drive measurable improvements in agreement.

Partner with research and modeling teams to translate eval findings into model, data and post-training priorities.

Scale human judgment into automated measurement (LLM-as-a-judge, auto-metrics) and validate automated scores against human ground truth.

Lead through collaboration, mentoring other content engineers on eval craft and rubric design.

Stay ahead of the generative media landscape, benchmarking against competitive and open-source model output.

Deliver high-quality evaluation work on model and launch timelines in a fast-paced, dynamic environment.

Minimum Qualifications:

10+ years of experience in video production, content strategy, editorial standards, media evaluation or relevant fields

Experience authoring evaluation rubrics for video and/or image quality, including dimension design, rating scales, tie-breaking rules and annotator guidelines

Hands-on video production expertise, direction, shooting, editing, post and/or VFX, with the craft vocabulary to diagnose quality failures precisely

Experience evaluating generative media output (text-to-video, image-to-video, video-to-video, text-to-image) and diagnosing model failure modes

Experience partnering with AI/ML research or modeling teams, translating evaluation results into training, data or model-behavior recommendations

Experience running human evaluation programs at scale: rater calibration, inter-rater reliability, golden sets, quality audits

Experience leveraging quantitative insights to inform content and quality decisions

Proven ability to build influence and drive alignment across…