Machine Learning Data Operations Manager

San Francisco
Artificial Intelligence and Data Science
Sirona’s mission is to make the highest quality healthcare available to everyone. We’re building a diagnostic engine that learns from and empowers the world’s most accurate radiologists–but enabling diagnosticians is just the beginning. Through our end-to-end workflow, we’re working to improve the quality and efficiency of the entire episode of care, simplifying the process of medicine and allowing doctors to focus on patients. We are interdisciplinary thinkers who are passionate about technology and medicine, and believe in the power of technology to protect and preserve human life. We’re in stealth mode and we’re hiring.

As part of the AI team, the ML Data Operations manager is responsible for supporting the Machine Learning Engineers’ and Data Scientists’ workflow. Building AI models for medical imaging requires large amounts of raw data and associated annotations. Ensuring the quality and ease of accessibility to this data is very important for building a streamlined modeling process. The Data and Annotations manager will take point on making sure this part of the AI team’s pipeline is as organized and efficient as possible.

Responsibilities

    • Develop annotation protocols for different imaging modalities and anatomies with our in-house radiologist
    • Manage and track progress of annotators and annotation firms
    • Work closely with our NLP and knowledge representation groups to understand and contribute to knowledge graph development, particularly as it relates to anatomy
    • Help manage and automate the QA process of annotations
    • Manage the cleansing, tagging, and organization of incoming images and medical data
    • Develop methods to optimize diversity and quality of training and validation datasets

Requirements

    • 3+ years professional experience in data operations and management
    • Experience managing within cross-functional teams
    • Basic proficiency in a data management programming tool (Python, SQL, ElasticSearch)
    • Preferred requirements:
    • Experience with DICOM data
    • Familiarity with cloud data platforms (AWS, GCP, Azure)

Benefits

    • Stock
    • Competitive salaries
    • Paid time off
    • Medical insurance
    • 401K
    • Apple equipment
    • Catered lunches and team events
    • Sponsorship for conferences