Cartesia
Tech / AI / Software
HumanDataOperationsManager
Neural analysis suggests this role is
optimal for Mid candidates.
“Human Data Operations Manager at Cartesia. Skills: design, scale, and operate global scaled evaluation workforce, end-to-end workforce system ownership, translating ambiguous product needs into operational workflows, partnering across product, engineering, data, and customer-facing teams. design, scale, and operate Cartesia's global scaled evaluation workforce. own the end-to-end workforce system: hiring pipelines, vendor strategy, workforce planning, quality control, and operational performance”
Industry & Context.
systems thinking; translating ambiguous product needs into operational workflows; problem-solving
execution speed is paramount, high bar
What They're Looking For.
Must Have
5+ years in operations, workforce management, or data annotation systems, Experience managing large contractor or vendor-based workforces, Proven ability to scale operations from zero to production, Systems thinking with the ability to design scalable operational frameworks, analytical skills with comfort around metrics like inter-rater reliability, precision, and throughput, Ability to execute quickly under ambiguity with close attention to quality and edge cases
Nice to Have
Experience in AI/ML data operations or evaluation pipelines, Background in audio, speech, or language-related workflows, Familiarity with QA systems and annotation tooling, Experience with marketplace platforms such as Upwork or Mercor, Exposure to multilingual operations
What You'll Do.
and operate Cartesia's global scaled evaluation workforce
own the end-to-end workforce system: hiring pipelines
and operational performance
build a production system of humans-in-the-loop for AI
translate ambiguous product needs into operational workflows
partner across product
and customer-facing teams to support real-world evaluation at scale
design and implement workforce structure across languages
and leads for TTS products
build capacity models to support continuous eval pipelines and data production workflows
own relationships with vendors such as data annotation firms and contractor platforms
negotiating rate cards
and throughput guarantees
or hybrid workforce models and continuously benchmark cost and performance across regions
design multi-layer QA systems spanning self-checks
define and track inter-rater reliability
error rates by category
and annotator-level performance distributions
build escalation and retraining workflows to maintain quality at scale
run day-to-day operations including task allocation
build systems to reduce evaluator fatigue
and maintain consistency across large-scale evaluations
partner with tooling teams to improve evaluator UX and with data teams to ensure clean
structured outputs for model training
How You'll Work.
Team & Collaboration
partnering across product, engineering, data, and customer-facing teams; partner with tooling teams; partner with data teams
Full Job Description
ABOUT CARTESIA Our mission is to architect AI that learns from and interacts with the world like humans do. We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences. We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI. The Role We are looking for a Human Data Operations Manager to design, scale, and operate Cartesia's global scaled evaluation workforce. This role sits at the intersection of product operations, data operations, and vendor management, and directly impacts model quality and customer outcomes. You will own the end-to-end workforce system: hiring pipelines, vendor strategy, workforce planning, quality control, and operational performance. You are building a production system of humans-in-the-loop for AI, translating ambiguous product needs into operational workflows and partnering across product, engineering, data, and customer-facing teams to support real-world evaluation at scale. Your Impact - Design and implement workforce structure across languages, skill tiers, and use cases, including evaluators, auditors, and leads for TTS products - Build capacity models to support continuous eval pipelines and data production workflows - Own relationships with vendors such as data annotation firms and contractor platforms, negotiating rate cards, SLAs, and throughput guarantees - Decide on build, buy, or hybrid workforce models and co
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