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This position was posted on April 17, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!

Cartesia Inc. logo

Data Quality Operations Analyst (Contract)

Job Overview

Location

*HQ - San Francisco, CA

Job Type

Contract

Category

Data & Analytics

Date Posted

April 17, 2026

Full Job Description

📋 Description

  • The Data Quality Operations Analyst (Contract) role at Cartesia Inc. is critical to ensuring the integrity and reliability of audio and text datasets used to train cutting-edge AI models. As the company scales its data pipelines, this position reduces the auditing burden on core research teams while upholding rigorous quality standards across multilingual workflows.
  • Day to day, the analyst will audit large-scale data deliveries from vendors and internal sources, create and refine quality guidelines tailored to specific datasets, provide structured feedback to external vendors and internal teams, and review and approve voice recordings from talent across various locales to ensure linguistic and technical accuracy.
  • Cartesia Inc. is a research-driven AI company founded by Stanford AI Lab PhDs who pioneered State Space Models (SSMs). Backed by top-tier investors including Index Ventures and Lightspeed, the company builds efficient, large-scale foundation models with a focus on human-like AI interaction, combining deep technical expertise with design-minded product engineering.
  • In this role, the analyst will develop expertise in data quality assurance for AI training data, gain experience with multilingual audio and text datasets, refine skills in vendor coordination and feedback delivery, and contribute directly to the reliability of frontier AI models through meticulous operational excellence.

Skills & Technologies

Onsite
$25-40/hr
Degree Required

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Cartesia Inc.
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About Cartesia Inc.

Cartesia Inc. builds real-time multimodal AI infrastructure that converts speech to text, text to speech, and audio to structured data with low latency. Its streaming APIs and edge-optimized models let developers embed voice capabilities into applications for customer support, transcription, accessibility, and IoT devices. The company emphasizes privacy, on-device processing options, and pay-as-you-go pricing.

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