Tech Lead Manager, Data Infrastructure

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.

Data is the lifeblood of our models, and we are looking for a TLM, Data Infrastructure to own the strategy and execution for all data at Cartesia. This is a critical leadership role, where you will be responsible for building and managing the datasets that power our cutting-edge research. You will lead a talented team of data engineers and specialists to acquire, process, and curate massive multimodal datasets. Your vision will directly shape the capabilities and quality of our foundational models.

• Define Cartesia’s overall multi-modal data strategy across pre-training and post-training, including human, synthetic, and web-scale data sources.

• Lead, manage, and mentor a team.

• Design and oversee the construction of robust, scalable data pipelines for text, audio, and video.

• Establish and enforce rigorous standards for data quality across the organization.

• Deeply understand how data affects model capability and proactively identify and source novel datasets.

• Manage relationships and budgets with external data vendors and partners.

• Technical expertise in large-scale data engineering.

• Familiarity with building datasets for and evaluating generative models.

• Leadership skills to grow and guide a high-impact data team.

🏢 We’re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.

🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.

🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.