Intuitive
Healthcare
DataEngineer(MLPlatform&DataFoundations)
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer (ML Platform & Data Foundations) at Intuitive. Skills: Data Engineering, ML Platform, Data Foundations, image data, video data, data pipelines, machine learning applications. Build and maintain data pipelines for image and video datasets used by ML models. Handle visual data ingestion, processing, validation and storage across system”
What You'll Achieve.
ML scientists can easily access trusted, well -organized image and video datasets; Data pipelines are reliable, observable, and scalable; Data quality issues are detected early and resolved quickly; The data platform accelerates ML development and deployment
Industry & Context.
rigor
proof of vaccination against certain diseases including COVID-19, U. S. Export Controls Disclaimer
What They're Looking For.
Must Have
3+ years of experience as a Data Engineer or in a similar role, primarily working with image or video data, proficiency in Python, Experience with cloud data platforms (AWS or GCP), Experience in Docker and Linux, Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
Nice to Have
Advanced degree or relevant certifications are a plus, but not required
What You'll Do.
Build and maintain data pipelines for image and video datasets used by ML models
Handle visual data ingestion
validation and storage across system
Extract and organize large media files and related metadata
Optimize data systems for performance and reliability including handling large binary data
Debug and fix issues in data pipelines and datasets
Organize datasets so they can be reliably used for model training and evaluation
Define and maintain schemas
and data documentation
Implement data quality checks
validation frameworks
Support data versioning
and reproducibility across evolving datasets
Partner closely with ML scientists to understand data requirements
Prepare and maintain datasets used for training and testing models
Support ML workflows by ensuring consistent
high-quality data inputs
Enable smooth handoff from experimentation to production
Collaborate with product
and engineering teams to align data solutions with business needs
Establish best practices for data modeling
Contribute to architectural decisions for data and ML platforms
How You'll Work.
Team & Collaboration
Work closely with ML scientists, data scientists, and software engineers; Collaborate with product, analytics, and engineering teams
Full Job Description
It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care , our technologies—like the da Vinci surgical system and Ion —have transformed how care is delivered for millions of patients worldwide. We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world. The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life. If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare , you’ll find your purpose here. Primary Function of Position We are looking for a Data Engineer to build and own the data foundations that power machine learning and analytics, with a strong focus on image or and video data. This role is focused on designing pipelines to ingest, process, and organize large-scale visual datasets for machine learning applications . You will work closely with ML scientists, data scientists, and software engineers to ensure data is reliable, discoverable, and production ready. What Success Would Look Like: * ML scientists can easily access trusted, well -organized image and video datasets -documented data * Data pipelines are reliable, observable, and scalable * Data quality issues are detected early and resolved quickly * The data platform accelerates ML development and deployment Essential Job Duties * Data Platform & Pipelines * Build and maintain data pipelines for image and video datasets used by ML models * Handle visual data ingestion, processing, validation and storage across system * Extract and organize
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