Product Operations Lead

About Cartesia

Our mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.

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.

Cartesia is seeking an entrepreneurial Product Operations Lead to spearhead data collection and evaluation initiatives that directly power our voice AI models. You'll work closely with our GTM, engineering and research teams to design, build, and scale evaluation frameworks and data collection systems that push the boundaries of what's possible with voice AI technology.

This is a highly strategic, 0-to-1 role designed for someone with strong analytical foundations who thrives at the intersection of product strategy and operations. You'll be responsible for creating novel evaluation methodologies, building scalable vendor and contractor systems from scratch, and solving complex operational challenges that directly improve our voice AI model performance and customer outcomes.

What You'll Do

Product Strategy & Customer-Facing Evaluations

• Own the strategy and roadmap for evaluation systems that demonstrate voice AI model performance on customer-specific use cases

• Define and align on key evaluation metrics that capture model quality and customer impact

• When customers have specific phrases or scenarios they care about, rapidly spin up evaluation systems to test performance and identify improvement opportunities

• Build strong relationships with customers to understand their evaluation needs and translate them into concrete technical requirements

• Lead cross-functional workstreams across GTM, Engineering, and Research to design evaluation frameworks that scale

Vendor & Data Operations

• Systematically identify, evaluate, and build relationships with data vendors to secure high-quality voice datasets that meet technical requirements and budget constraints

• Negotiate contracts and manage ongoing vendor relationships to ensure consistent quality and delivery

• Create repeatable playbooks for vendor evaluation, onboarding, and performance management

• Use data to guide decision making, diagnose vendor issues, and measure performance across the supply chain

Contractor Network & Team Building

• Design and implement systems to hire, onboard, and manage contractors for data collection, annotation, and evaluation tasks

• Scale our contractor network to improve quality and reduce costs while maintaining high standards

• Create high-conversion onboarding experiences and incentive systems that attract and retain top-quality contractors

• Build screening workflows that identify, evaluate, and onboard only the best contributors

Cross-functional Partnership & Execution

• Partner closely with engineering and research teams to ensure evaluation systems integrate seamlessly with training pipelines and model development

• Spot failure points early—whether in sourcing, quality, or process—and take ownership of fixing them

• Use metrics to track performance, prioritize work, and make decisions about where to invest and what to build next

• Know when to move fast and when to slow down for alignment, with a bias for rapid prototyping and iteration

What You'll Bring

• 4+ years of professional experience: Ideally 2+ years at a top-tier consulting, investment banking, or private equity firm and 2+ years at a technical company or in product/operations roles

• Systems thinking - able to spot leverage points in complex processes, evaluate second and third order effects, and resolve bottlenecks effectively