Applied Researcher
Cartesia
Applied Researcher
Cartesia
Develops foundation models with subquadratic architectures
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.
You will be responsible for leading research at the frontier of realtime conversation and human AI interaction. You will contribute across the stack to novel architectures, data, and evals for realtime audio, and translate them into state-of-the-art models used in voice agents around the world.
Architect and develop new architectures for realtime audio understanding, generation, and speech-to-speech models that reason jointly over multiple modalities in realtime
Contribute to frontier multimodal and multilingual datasets for pre-training and post-training, including curating data mixes and developing new methods for synthetic data generation and annotation
Set new standards for how we evaluate and benchmark our audio models
Strong applied mindset and ability to balance scientific novelty with product impact.
Excited and able to work across the stack from infra, to data, to evals, to architecture to solve customer problems and build state-of-the-art models.
Deep expertise in deep generative modeling. Previous experience in audio understanding, audio generation, speech-to-speech, or language modeling preferred but not required.
Experience with large-scale training, GPU/TPU acceleration, and model optimization.
Note: Cartesia participates in E-Verify and will provide the federal government with Form I-9 information to confirm employment eligibility after hire.
🏢 In-office policy: We’re an in-person team based out of offices in 🇺🇸 San Francisco, 🇬🇧 London and 🇮🇳 Bangalore. We love being in the office, hanging out together, and learning from each other every day.
🌎 Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call.
🚢 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.
💰 Compensation Competitive base salary alongside attractive equity package.
🩺 Health Insurance Fully covered medical insurance along with dental and vision for you and your family.
🧑🧑🧒🧒 Parental Leave 9 weeks paternity & 12 weeks maternity leave
🏦 401(k)
🚆 Commuter Allowance A monthly stipend to help you get to and from the office.
🏖️ Flexible PTO Take as much time as you need to recharge your batteries.
🍲 Meals & Snacks Lunch, dinner and plenty of snacks, provided daily.
🦖 Your own personal Yoshi
Cartesia is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other legally protected status.
Cartesia.ai develops advanced AI foundation models using new subquadratic architectures and state space models. Its models are designed as underlying systems that can be adapted for many applications and are released in part under open-source licenses (e.g., Apache 2.0), with licensing, partnerships, and consulting as revenue streams. The company’s products work by providing large, adaptable AI models that clients can license or customize for specific needs, enabling faster processing and efficient inference compared to traditional designs. Cartesia differentiates itself from competitors by using subquadratic, state space approaches instead of relying mainly on standard Transformer models, and by combining open-source releases with enterprise partnerships. The goal is to help businesses and research institutions access powerful, adaptable AI capabilities while building a community around its technology and sustaining revenue through licensing and services.
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