Back to jobs

Software Engineer, Data Infrastructure

San Francisco, California, United States

Pay
Salary not listed in the saved posting
Work setup
Unconfirmed
Employment
Unconfirmed

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
🌎 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.
Read the full posting
Apply at Cartesia

What you’ll work on

Full posting

Data is the lifeblood of our models, and we are looking for a Software Engineer, Data Infrastructure to own the strategy and execution for all data at Cartesia.

  • You will design scalable systems to acquire, process, and curate massive multimodal datasets while partnering closely with research and inference teams.

  • Define Cartesia's multi-modal data strategy across pre-training and post-training, spanning human, synthetic, and web-scale sources, with particular depth in audio.

  • Partner closely with research and inference teams so data systems are co-designed with training and serving infrastructure (batching, GPU-aware loading, evaluation pipelines).

From the employer’s posting
Data is the lifeblood of our models, and we are looking for a Software Engineer, Data Infrastructure to own the strategy and execution for all data at Cartesia. In this highly impactful role, you will build and evolve the datasets that power our cutting-edge research. You will design scalable systems to acquire, process, and curate massive multimodal datasets while partnering closely with research and inference teams. Your work will directly shape the capabilities and quality of our foundational models.
About the Role Data is the lifeblood of our models, and we are looking for a Software Engineer, Data Infrastructure to own the strategy and execution for all data at Cartesia. In this highly impactful role, you will build and evolve the datasets that power our cutting-edge research. You will design scalable systems to acquire, process, and curate massive multimodal datasets while partnering closely with research and inference teams. Your work will directly shape the capabilities and quality of our foundational models. Your Impact
Your Impact Define Cartesia's multi-modal data strategy across pre-training and post-training, spanning human, synthetic, and web-scale sources, with particular depth in audio. Design and operate scalable, high-throughput data pipelines for text, audio, and video — covering ingestion, preprocessing, augmentation, dataset versioning, and data loading for training.
Design and operate scalable, high-throughput data pipelines for text, audio, and video — covering ingestion, preprocessing, augmentation, dataset versioning, and data loading for training. Partner closely with research and inference teams so data systems are co-designed with training and serving infrastructure (batching, GPU-aware loading, evaluation pipelines). Establish and enforce rigorous standards for data quality, with a tight feedback loop between dataset characteristics and model behavior.

What you’ll bring

All qualifications

Core experience

  • Hands-on experience with ML data infrastructure: training data pipelines, dataset versioning, large-scale data loading, and the interplay between data systems and model training and inference.
  • Experience leading cross-functional technical efforts in a fast-moving, research-driven environment.
  • Familiarity with building and evaluating datasets for generative models and reasonable working knowledge of how they’re trained and inference.
Qualification wording
Hands-on experience with ML data infrastructure: training data pipelines, dataset versioning, large-scale data loading, and the interplay between data systems and model training and inference.
Experience leading cross-functional technical efforts in a fast-moving, research-driven environment.
Familiarity with building and evaluating datasets for generative models and reasonable working knowledge of how they’re trained and inference.

Tools in this posting

  • Databricks
Source — Tool mentions in context
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

About Cartesia

Our mission is to architect AI that learns from and interacts with the world like humans do.

In the employer’s words · Read in context

Job description

View original posting ↗

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

Data is the lifeblood of our models, and we are looking for a Software Engineer, Data Infrastructure to own the strategy and execution for all data at Cartesia. In this highly impactful role, you will build and evolve the datasets that power our cutting-edge research. You will design scalable systems to acquire, process, and curate massive multimodal datasets while partnering closely with research and inference teams. Your work will directly shape the capabilities and quality of our foundational models.

Your Impact

  • Define Cartesia's multi-modal data strategy across pre-training and post-training, spanning human, synthetic, and web-scale sources, with particular depth in audio.

  • Design and operate scalable, high-throughput data pipelines for text, audio, and video — covering ingestion, preprocessing, augmentation, dataset versioning, and data loading for training.

  • Partner closely with research and inference teams so data systems are co-designed with training and serving infrastructure (batching, GPU-aware loading, evaluation pipelines).

  • Establish and enforce rigorous standards for data quality, with a tight feedback loop between dataset characteristics and model behavior.

  • Identify and source novel datasets; manage relationships and budgets with external data vendors and partners.

What You Bring

  • Hands-on experience with ML data infrastructure: training data pipelines, dataset versioning, large-scale data loading, and the interplay between data systems and model training and inference.

  • Working knowledge of multimodal data, i.e. audio: formats, preprocessing, augmentation, and large-scale storage and streaming patterns.

  • Strong modern engineering execution: clean, well-tested code, fluency with current tools, and a willingness to pick the right tool for the problem rather than defaulting to familiar patterns.

  • Experience leading cross-functional technical efforts in a fast-moving, research-driven environment.

  • Familiarity with building and evaluating datasets for generative models and reasonable working knowledge of how they’re trained and inference.

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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

San Francisco, California, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization
🏢 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.
Status in our records
Active
First seen by us
May 13, 2026
Recorded sightings
94
Last seen by us
Oct 7, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.