Tech Lead Manager, Data Infrastructure
cartesia
OnSite
*HQ - San Francisco, CA
Engineering
Data
Uncategorized
Job Score
90 pts
On-site model (+70)
Engineering (+10)
Data (+10)
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 TLM, Data Infrastructure to own the strategy and execution for all data at Cartesia. This is a critical leadership role, where you will be responsible for building and managing the datasets that power our cutting-edge research. You will lead a talented team of data engineers and specialists to acquire, process, and curate massive multimodal datasets. Your vision 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.
Lead, mentor, and eventually manage a team of engineers building dataset and ML data infrastructure.
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.
Track record leading and growing a high-impact engineering team 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.
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.
About Data
The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.
Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.
The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.
About Engineering
Software Engineering goes beyond traditional development, focusing on scalability, performance, and system architecture. Software engineers are responsible for designing infrastructures that support millions of simultaneous users.
Skills include microservices architecture, DevOps, cloud computing, application security, and performance optimization. Knowledge of containerization (Docker, Kubernetes) and CI/CD is increasingly required.
Senior software engineers are rare and highly compensated professionals, with opportunities at major global tech companies.
Discover Other Areas
Understand the scope of work, key skills, and tools used in different career areas.
About Social Media
The Social Media area is one of the most dynamic and constantly evolving fields in digital marketing. Social media professionals are responsible for creating, managing, and optimizing brand presence on digital platforms, building engagement and community with the target audience.
Key skills include social media management (Instagram, TikTok, LinkedIn, Facebook, YouTube), social media content creation, community management, paid social media (Meta Ads, LinkedIn Ads, TikTok Ads), metrics analysis, and strategic planning. Tools like Hootsuite, Sprout Social, Buffer, Later, and analytics platforms are essential.
Social media professionals in technology companies are highly valued, especially those who master paid social, social media analytics, and content strategies for different platforms. The field offers opportunities from analyst to head of social media, with a focus on growth, engagement, and return on investment.
About Mobile Development
Mobile Development is one of the most dynamic and constantly evolving fields in the technology market. With billions of smartphones worldwide, the demand for qualified mobile developers continues to grow exponentially.
Key stacks include Flutter (Dart), React Native (JavaScript/TypeScript), Kotlin (Android native), Swift (iOS native), and hybrid frameworks like Ionic and Capacitor. Knowledge of mobile architecture (MVVM, Clean Architecture), mobile CI/CD (Fastlane, Bitrise, Codemagic), and App Store/Google Play publishing are essential.
Senior mobile developers are highly valued professionals, with competitive salaries and many remote work opportunities at international companies. Specializing in cross-platform or native is a strategic career decision.
About Automation Engineer
The Automation Engineer is the professional responsible for designing, developing, and implementing solutions that automate manual and repetitive processes in IT, infrastructure, testing, and operations. They combine programming knowledge with DevOps and SRE vision to eliminate manual tasks and increase operational efficiency.
Key skills include Infrastructure as Code (Terraform, Ansible, Pulumi), CI/CD (Jenkins, GitHub Actions, GitLab CI), test automation (Selenium, Cypress, Playwright), network automation (Netconf, SDN), RPA (UiPath, Power Automate), and scripting (Python, Bash, PowerShell). Knowledge of Kubernetes, GitOps (ArgoCD, Flux), and automation platforms is a differentiator.
Automation Engineers in technology companies are highly valued, especially those who can create automated deployment pipelines, self-healing infrastructure, and internal developer platforms (IDP). The field offers opportunities from junior automation engineer to automation architect and head of automation.
About Design
The Design field, especially UX/UI and Product Design, has experienced significant growth in recent years. With accelerated business digitization, the demand for professionals who can create intuitive and pleasant digital experiences has never been higher.
Key skills include Figma, Sketch, Adobe XD, user research, design thinking, prototyping, and system design. Product designers are increasingly valued for their direct impact on business results.
Remote work has opened doors for Brazilian designers to work for global companies, with competitive salaries in dollars and euros.
About Product Management
Product Management is one of the most strategically relevant areas in technology organizations. The Product Manager is responsible for defining product vision, prioritizing features, and coordinating multidisciplinary teams to deliver value to users.
Essential skills include strategic thinking, data analysis, communication, leadership, and technical knowledge. Tools like Jira, Confluence, Miro, and analytics platforms are fundamental in daily work.
Salaries for PMs range from entry-level to senior positions at major tech companies, with growing opportunities for international remote work.