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Engineering Manager, Data

Lead a data team at Cartesia to enhance the quality of multimodal AI training data and infrastructure.

Location
*HQ - San Francisco, CA
Compensation
Not disclosed
Level
lead
Type
full time · On-site

Posted by employer 3 months ago

First seen on Joblaze 1 month ago

Last verified on the company career page 20 hours ago

Apply at Cartesia → Save job Scanned from cartesia.ai

Role intensity

10% coding — mostly leadership/strategy

Requirements

Experience
6+ years
Education
PhD
Visa
Sponsorship available

Not disclosed in this posting: compensation.

Benefits

Meals & Snacks 401(K) Flexible PTO Commuter Allowance Health Insurance Parental Leave

Joblaze summary

In the role of Engineering Manager for Data at Cartesia, the individual will oversee a team focused on developing and maintaining robust data infrastructure while ensuring the quality of multimodal datasets. Key skills include hands-on experience with large-scale data systems and a proven track record in leading data teams, particularly in modeling contexts. This position is ideal for someone with significant management experience and a background in data-centric modeling, suited for a fast-paced, innovative environment. Cartesia emphasizes collaboration and rapid execution, fostering a culture of support and inclusivity.

Joblaze insights

  • Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Cartesia's careers page October 27, 2026.
  • AI/ML appears in 26.8% of 598 comparable lead management roles in United States; Data Infrastructure appears in 0.2% of 598 comparable lead management roles in United States.

Quick facts

Is the Engineering Manager, Data role remote?
No — this is an on-site role in *HQ - San Francisco, CA.
How much experience is required?
At least 6 years of relevant experience for this Engineering Manager, Data role.
Where is the role based?
Cartesia is hiring for this position in *HQ - San Francisco, CA.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Data Infrastructure, data-centric modeling, multimodal data.
Does Cartesia sponsor work visas for this role?
Yes — the posting indicates visa sponsorship is available for the right candidate.
What seniority level is this role?
Cartesia targets lead candidates for this position.
Is this full-time or contract?
Full-time for this Engineering Manager, Data role at Cartesia.

From the original posting

About the Role

At Cartesia, the quality of our models is inseparable from the quality of our data. As we push the frontier of real-time multimodal AI, we're looking for a leader to own the systems, datasets, and research that make our training data exceptional.

You'll lead our Data team, responsible for three tightly connected areas:

  • Data infrastructure — web-scale processing and storage that keeps petabytes of multimodal data flowing reliably to the teams that depend on it.

  • State-of-the-art pre-training datasets — building the multimodal annotation models that understand who said what, when, and how, and curating the data mixes that shape model behavior.

  • Data-centric modeling — training and evaluating models to understand what actually makes data good, and turning those insights into better datasets.

You'll start by managing a team of 6–8 spanning core data infrastructure and individual modeling efforts, and grow it toward ~12 as our ambitions scale. This is a role for someone who has done this before: built and led a data team, shipped data at the scale modern models demand, and knows the difference between infrastructure that works in a demo and infrastructure that works at web scale.

Your Impact

  • Lead and grow a high-caliber team of data infrastructure engineers and data-focused researchers, splitting focus between shared infra and dedicated modeling teams.

  • Set the technical direction for how Cartesia processes, stores, and serves multimodal data at web scale.

  • Drive the creation of SOTA multimodal pre-training datasets — including the annotation models and curation strategies that determine what our models learn.

  • Establish a rigorous, empirical approach to data quality: training and evaluating models specifically to understand what makes data valuable, and feeding that back into dataset decisions.

  • Partner closely with our modeling and research teams to make sure data work translates directly into better models.

  • Hire, mentor, and develop engineers and researchers as the team scales from a handful of people to a full organization.

What You Bring

  • Proven management experience, including directly leading a data team of at least 6 people.

  • Hands-on familiarity with data infrastructure at scale — processing, storage, and the systems that make large-scale data usable.

  • A track record of building and leading data efforts, ideally in the context of a modeling project.

Nice-To-Haves

  • Previous modeling experience

  • Experience building data for a generative modeling organization.

  • Familiarity with multimodal data (audio, speech, and beyond).

🏦 401(k)

🦖 Your own personal Yoshi

Standard company text repeated across Cartesia's postings is omitted here.

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