Project Manager - Voice AI Data Operations (TTS / STT / RLHF)

About Arctic Engines

Arctic Engines is a specialized AI data services partner working with leading voice and speech AI companies. We deliver high-quality annotated datasets and human feedback workflows that train the next generation of voice models. We are currently expanding our delivery team to support our work, one of the world's foremost voice AI labs.

About the Role

We are looking for a hands-on Project Manager to own end-to-end delivery of voice annotation projects — including RLHF (Reinforcement Learning from Human Feedback), Text-to-Speech (TTS), Speech-to-Text (STT), and custom speech tasks. You will lead a pod of 5–15 annotators and QCs, drive quality and throughput targets, and act as the operational bridge between our delivery team and the client.

This is a delivery-heavy role for someone who has lived in spreadsheets, guideline documents, and QC reports — and enjoys it.

What You'll Do

• Own project delivery for voice annotation workstreams (RLHF, TTS, STT, custom) — daily targets, weekly milestones, and final dataset hand-off.
• Manage a team of 5–15 annotators and QCs — task allocation, shift planning, capacity utilization, performance reviews, and ramp-up of new joiners.
• Drive quality outcomes — partner with QC leads to monitor IAA (Inter-Annotator Agreement), error rates, and rejection patterns; run calibration sessions when scores drift.
• Translate client guidelines into operational SOPs — break down complex annotation specs into clear, repeatable instructions for the floor.
• Handle client coordination — receive guideline changes, rework requests, and clarifications from the client (escalations are co-handled with the founder); communicate impact back internally.
• Track and report — maintain dashboards on volume, quality, productivity, and project P&L; publish weekly status to leadership and client.

Continuously improve — identify bottlenecks, propose tooling or process changes, and run small experiments to lift throughput or quality.

Must-have

• 3–5 years of total experience, with 2+ years managing voice/speech annotation projects (TTS, STT, ASR, voice RLHF, prosody, phonetic transcription, or similar).
• Direct experience working with annotation platforms (Label Studio, CVAT, Prodigy, internal client tooling, etc.).
• Demonstrated track record of managing annotator pods (10+ people) and hitting quality and volume SLAs.
• Strong working knowledge of QC frameworks — IAA, gold sets, sampling-based audits, rework cycles.
• Comfort with spreadsheets/Google Sheets, basic data analysis, and reporting dashboards.
• Excellent written and spoken English — you'll be reading dense guideline documents and writing clear instructions.

Nice-to-have

• Exposure to RLHF preference labeling or human feedback for generative models.
• Familiarity with audio quality concepts (SNR, prosody, phoneme alignment, speaker diarization).
• Experience working with US/EU AI labs as clients.
• Working knowledge of multiple Indian or global languages (useful for multilingual voice projects).