Applied Researcher, Audio
Company websitecartesia.ai (Cartesia, opens in new tab)
Base salary $200K to $350K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
About this job
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.
About the Role
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.
Your Impact
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
What You Bring
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.
More Details
🏢 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.
Our Benefits (US Employees Only)
💰 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
Our Commitment to Equal Opportunity
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.
Source: Cartesia on Ashby · View original posting (opens in new tab)
This listingApplied Researcher, Audio$200K to $350K
Research Engineer, Data Infrastructure (Language Modeling)$200K to $350K
Enterprise Engineer$180K to $250K
Researcher, Evals$220K to $350K
Software Engineer, Data Infrastructure$180K to $250K
Inference Engineer$180K to $250K
Researcher, Models$180K to $350K
Chart as a table
| Role | Published base |
|---|---|
| Applied Researcher, Audio (this listing) | $200K - $350K |
| Research Engineer, Data Infrastructure (Language Modeling) | $200K - $350K |
| Enterprise Engineer | $180K - $250K |
| Researcher, Evals | $220K - $350K |
| Software Engineer, Data Infrastructure | $180K - $250K |
| Inference Engineer | $180K - $250K |
| Researcher, Models | $180K - $350K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2025-09-16
Where this pay comes from
Location as the employer wrote it: *HQ - San Francisco, CA
USD 200,000 – 350,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
