Audio Annotation Analyst

Overview

We need an analyst who can execute both comparative listening evaluations and detailed musicological captioning  will run structured preference tasks, craft grounded long-form descriptions of tracks, and keep throughput, quality, and metadata spotless for model-training partners.

• Follow structured rubrics covering overall preference, holistic ratings, appeal axes, adherence checks, and engagement scoring for A/B and A/B/X tasks.
• Document concise rationales for every overall preference choice, calling out musical, stylistic, or technical drivers.
• Ensure smooth playback verification (scrubbing, repeated listens) and confirm clips align with task prompts before logging results.
• Tag each submission with the correct prompt, model version, rater , and timestamp to maintain metadata fidelity.
• Surface anomalies - audio defects, unclear prompts, UI bugs - to the lead so tasks can be recycled or corrected quickly.

• Produce 300- to 500-word captions per track that describe structure, timbre, instrumentation, stylistic influences, and emotional arcs in present tense.
• Create timeline callouts (start time, section type, narrative notes, instrument/vibe tags) plus summary tables for genre, instrumentation, mix, vibe, quality, and wow factor.
• Apply the Foreground Rule and grounded subjectivity guidelines to stay concise, accurate, and conversational.
• Maintain throughput targets (20 - 30 minutes per track) while protecting quality.
• Contribute calibration feedback by highlighting edge cases, ambiguous cues, or instructions that need refinement.

• Participate in pilot runs (50 - 500 tasks), logging timing, UI, and instruction issues for iteration before scale-up.
• Complete gold-standard qualification sets and ongoing drift checks; incorporate reviewer notes immediately into future work.
• Keep dashboards or trackers updated with daily task counts, rejection reasons, and rework so leads can forecast burn-down.
• Collaborate with engineers or ops partners to request UI tweaks, metadata fixes, or schema updates without slowing delivery.

• 2+ years in human annotation, music journalism, audio QA, or related analyst roles.
• Demonstrated ear for musical structure, instrumentation, and production details across
• Comfortable working inside configurable annotation tools, spreadsheets, or content management systems.
• Strong written communication with the ability to summarize subjective listening impressions using precise, grounded language.
• High attention to detail for metadata tagging, file naming, and prompt/model crosschecks.
• Reliable remote setup with headphones suited for repeat listening sessions and the focus to handle long-form writing blocks.

• Background in music theory, ethnomusicology, or audio engineering.
• Experience supporting generative audio, recommender systems, or creator tools.
• Working knowledge of SQL, Python, or automation scripts to accelerate QC or reporting.
• Familiarity with data privacy or content sensitivity guidelines for global annotation programs.

• Completes assigned preference tasks with