Machine Learning Engineer, Data

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.

To build truly global AI, our models must be trained on data that reflects the world's diversity of languages and cultures. We are searching for a Machine Learning Engineer to own the quality and coverage of the data behind our models. You will be our in-house expert on global data, ensuring our models perform exceptionally well across dozens of languages. You have a keen eye for linguistic nuance, and a passion for building inclusive and representative datasets at scale.

Design and build large-scale datasets for model training.

Build evaluations of speech models, both via manual annotation and at scale with automated metrics.

Implement techniques for steering data generation to improve model intelligence through data and mitigate bias.

Build automated quality control systems to validate and filter generated data

Partner with product teams to ensure support for key languages and markets.

Experience building or working with large multilingual datasets

Experience with generative models (speech, text, or multimodal).

Ability to help guide human annotation and evaluation across multiple languages.

Strong applied ML background with a focus on data-centric approaches.

Excitement for building scalable systems that bridge research and production.

🏢 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.