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$200k–$350k/yr
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 Stan…
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · Remote OK
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San Francisco, California, United States · On-site
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The role involves designing and implementing post-training capabilities for generative audio models, including SFT, RL, and evaluation pipelines. You will collaborate with product teams to translate customer needs into concrete research plans and production-ready model improvements.
Candidates need strong fundamentals in software engineering and machine learning, with specific experience training and debugging generative models. Proficiency in building large multilingual datasets and a focus on solving real-world customer problems are essential.
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.
On the Audio Post-Training team, you’ll be building and improving the capabilities that define how the rest of the world interacts with our generative audio models. This team is where customer needs meet research, and covers the full spectrum of modeling from ideation through productionization. On any given day, you might design evaluations to reliably measure new capabilities, build processing pipelines to improve data quality, experiment with finetuning and reinforcement learning approaches to refine model behavior, and more.
This role is broad, and cross functional. Members of this team should combine broad research experience with a deep care about building to solve for customer needs and a strong sense of end-to-end ownership. You should be excited to synthesize customer complaints into a holistic understanding of capability gaps, to drive research efforts across data, model training, and evaluation to close those gaps, and to communicate those improvements to product and customer stakeholders. Ultimately, you will be responsible for creating the model experience that the rest of the world sees.
Collaborate with product teams to understand and prioritize customer asks
Cut through the ambiguity of vaguely described behavioral problems to make concrete research plans.
Ideate and experiment across the full modeling stack, including data processing, synthetic data, SFT, RL, and evals to solve for high priority model capabilities
Root cause failures in production models and understand how to fix them in future model iterations
Decide which features and capabilities are ready for public launch
Strong fundamentals in software engineering, machine learning, debugging complex systems, and the ability + desire to learn quickly.
Experience building and ensuring quality of large multilingual datasets.
Experience training and debugging generative models (speech, text, or multimodal), especially SFT, RL, synthetic data, and evaluation (both human and automated).
Excitement about solving problems grounded in real customer needs, not just benchmarks.
Bonus points if you have native proficiency in other languages!
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.
Architecting AI that learns and interacts like humans
Our mission is to architect AI that learns and interacts like humans. Try Sonic and Ink at https://play.cartesia.ai
