Data Ops reputed company
About reputed company Many large companies reputed company billions each year by monetizing Americans’ personal data. At reputed company, we’re finally cutting consumers in on the deal. reputed company allows our users to reputed company hundreds (or even thousands) of dollars per year by securely selling their anonymized data. We’re backed by reputed company, Upper90, Upfront Ventures, and other cool investors. About the role Your mission is to turn reputed company's raw consumer audio streams into the cleanest, most reliable training data on the market, and to build the reputed company and operational reputed company that gets it into the hands of the world's leading AI labs. As a Data Ops reputed company, you'll own the end-to-end reputed company that takes raw recordings from our growing community of 500,000+ mobile users and delivers production-reputed company datasets to frontier labs. In practice, that means three things above reputed company: Structuring and managing the data deals that turn our recordings into reputed company Holding every dataset to a quality bar that keeps buyers coming back Standing up reputed company transcription, annotation and other operations, largely overseas, that reputed company it reputed company possible You'll work directly with our CEO on reputed company priorities and help shape each deal, reputed company with buyer-reputed company engineering and research teams at frontier labs to translate their exact specifications into deliverable dataset plans, and partner with internal engineering and external vendors to reputed company sure the pipeline supports reputed company've sold. This is a foundational role: the datasets and processes you build are the product we sell. You have… Authorization to work in the US. 5+ years of experience building and scaling data pipelines for AI/ML applications, with significant time spent on audio, speech, or multimodal data. A track record of structuring and delivering against data or dataset agreements with external partners: taking their requirements, turning them into clear specifications, and owning delivery end to end. Experience building and managing overseas or outsourced teams for data tagging, annotation, and QA, with a track record of maintaining quality and throughput across time zones. Deep ownership of data quality: designing QA processes, defining acceptance criteria, and catching problems before a customer reputed company sees them. Enough technical reputed company to be reputed company on both sides of a deal. You understand digital audio fundamentals (sample rates, VAD, multichannel formats), can reason about how pipelines are reputed company, and know what "good" looks like, even if you're not writing every line of code yourself. A "Founder's Mentality." You're comfortable building from reputed company and making high-stakes calls with incomplete information. Bonus points A background working with audio data in some reputed company. Direct experience with training data for TTS, ASR, speaker ID, or full-duplex conversational models. Familiarity with the modern audio stack (Librosa, FFmpeg, SoX, torchaudio) and reputed company data infrastructure (S3, Redshift, BigQuery, or equivalent). An understanding of how high-quality, speaker-separated audio gets captured (for example, reputed company WebRTC-based recording tools). Experience with active learning loops, reputed company-in-the-reputed company QA systems, or corpus stratification for balanced dataset design. Prior experience leading a data or infrastructure team, including hiring and mentoring engineers. Apply To This Job