
Posted 2 months ago
Member of Technical Staff, Data Engineering
AI Summary
Owns the data pipelines and workflows that turn raw radiology data into high-quality training, evaluation, and production datasets for AI models.
About this role
About Cognita
Cognita’s mission is to increase the world’s access to healthcare. Radiology is (1) the first-line diagnostic specialty, (2) facing a worsening global workforce shortage, and (3) highly digitized, making it uniquely positioned for AI to have an enormous impact. Stage one of Cognita is focused on expanding access to radiology at scale.
Our founding team met at Stanford, where they laid the groundwork for applying comprehensive AI to radiology. Building on that foundation, Cognita develops vision-language models that read radiology studies the way radiologists do - interpreting the full study in clinical context - and generate draft results that make radiologists more efficient and accurate. In partnership with Radiology Partners, Cognita’s models are trained and validated on one of the world’s largest real-world radiology datasets.
About the Role
As a Member of Technical Staff in Data Engineering, you will own the systems and workflows that transform Cognita’s raw radiology data into high-quality datasets used to train, evaluate, and improve production AI models.
Your Impact
Build and operate pipelines that process large volumes of radiology data, including imaging studies, reports, and longitudinal priors.
Design data formats and representations that work efficiently for model training and evaluation.
Run large-scale data cleaning and normalization workflows to prepare datasets for training.
Ensure data is well-organized, versioned, and reproducible across training runs.
Partner closely with ML training engineers to enable efficient training workflows.
Debug data issues that surface during training, evaluation, or deployment.
What You Bring
We are not credential-driven. We only look for evidence of exceptional ability.
Strong experience building data pipelines or infrastructure for ML systems.
Experience handling large, messy, real-world datasets.
Ability to reason deeply about data quality, structure, and failure cases.
Comfort working in systems where requirements evolve as models improve.
Strong ownership mindset and attention to detail.
What Sets You Apart
Experience working with medical imaging, healthcare data, or regulated datasets.
Familiarity with ML training workflows and large-scale model development.
Experience incorporating human-in-the-loop feedback into data systems.
Experience operating data pipelines in production environments.
Our Culture
We’re an in-person team based in the San Francisco Bay Area. Working together every day helps us move faster, learn from each other, and build strong relationships. We believe the best work happens when great people are in the same room.
We build from first principles. We question assumptions, reason from fundamentals, and execute with speed and clarity, without sacrificing quality.
We operate as a true meritocracy. Impact matters, rather than optics. Feedback is direct, respect is non-negotiable, and we support each other with the ownership, trust, and resources needed to do the best work of our careers.
Every decision we make is grounded in supporting clinicians to improve patient outcomes.
Skills
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