Machine Learning Data Engineer - Obstetric Ultrasound

Machine Learning Data Engineer - Obstetric Ultrasound

Job Description Summary

We are seeking a highly skilled Data or MLOps Engineer with experience in medical imaging, machine learning, and cloud-based data infrastructure management to help configure databases and ML training pipelines in the cloud as part of an overall effort to develop algorithms for ultrasound image interpretation in obstetric and maternal health. The successful candidate will be responsible for database and compute configuration on Amazon Web Services (AWS), dataset transfer and organization, code repository setup and maintenance in GitLab, and coordination and support for multiple teams collaborating on this cloud platform across geographic regions.

Company Overview

GE HealthCare is a leading global medical technology, pharmaceutical diagnostics, and digital solutions innovator dedicated to providing integrated solutions, services, and data analytics to make hospitals more efficient, clinicians more effective, therapies more precise, and patients healthier and happier. Serving patients and providers for more than 100 years, GE HealthCare is advancing personalized, connected, and compassionate care, while simplifying the patient’s journey across the care pathway.

Job Overview

The GE HealthCare Ultrasound business consists of ultrasound consoles, handheld ultrasound devices, and ultrasound IT solutions across five market segments. There is a strong emphasis on the development of AI solutions for our ultrasound products so we can create additional value for customers and patients.

Responsibilities

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• Configure new projects on AWS, including creation of databases for both tabular and imaging data, with appropriate consideration for IAM across multiple teams.
  
• Coordinate transfer of large volumes of data from multiple sources into AWS.
  
• Design and implement data ETL / preprocessing pipelines to prepare data for efficient use in ML training pipelines.
  
• Manage and optimize the computational resources used by team members.
  
• Support management of data labeling platforms (e.g., V7, LabelBox) to streamline data annotation processes.
  
• Help manage collaborations between geographically distributed teams within the platform, providing technical support as needed.
  
• Help streamline the process of dataset development, model training, and performance assessment, including model version control and tracking.
  
• Contribute to cost‑effective use of cloud resources through oversight of compute usage and minimization of storage footprint.
  
• Collaborate with product, clinical, and regulatory teams on the clinical validation of AI software for marketing approval.
  
• Stay up‑to‑date with the latest advancements and tools available for use by the ML team.
  

Required Knowledge / Skills / Abilities

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• Experience with MLOps practices, including ETL pipelines, Docker, Kubernetes, and version control systems (e.g., Git).
  
• Experience with cloud platforms (e.g., AWS, GCP) and infrastructure‑as‑code tools.
  
• Background in ultrasound or other medical imaging modalities and related software tools such as DICOM, pydicom, opencv, or ITK.
  
• Experience with Python and the scientific stack (numpy, scipy, matplotlib, pandas, scikit‑learn, scikit‑image).
  
• Experience with one major deep learning framework (TensorFlow, Keras, PyTorch, etc.).
  
• Experience writing production code and leading code review processes.
  
• Strong teamwork ethic, communication skills, and passion for learning.
  
• Substantial experience solving complex real‑world data problems in a commercial environment.
  

Basic Qualifications

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• A 2.1 or 1st degree in a technical discipline, or an MSc or PhD in a relevant field (Computer Science, Electrical/Biomedical Engineering, Physics, Neuroscience, Statistics, Mathematics).
  
• Excellent programming and software engineering skills, with a focus on data engineering.
  
• Highly proficient in Python and SQL.
  

Eligibility Requirements

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• This position is based in the United Kingdom only. Legal authorization to work in the U.K. is required.
  
• Must be willing to travel as required.
  

Desirable Skills

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• Practical experience managing large volumes of data from complex real‑world problems in a commercial setting.
  
• Knowledge of designing, building, and maintaining efficient and robust data architectures.
  
• Ability to apply software engineering methodologies to complex real‑world problems.
  
• Experience in medical imaging, ideally ultrasound.
  
• Background in BI/reporting.
  
• Experience with development under ISO13485.
  

Personal Attributes

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• Excellent interpersonal and communication skills at all levels of an organization.
  
• Self‑starter—requires minimal direction to accomplish goals, proactive and enthusiastic.
  
• Strong team player—collaborates well with others to solve problems and incorporates input from various sources.
  
• Exceptional organizational skills and attention to detail.
  

Inclusion and Diversity

GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

Behaviours

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership—always with unyielding integrity.

Total Rewards

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world‑changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration, and support.

Relocation Assistance

No.

Seniority level

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• Mid–Senior level
  

Employment type

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• Full‑time
  

Job function

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• Engineering and Information Technology
  

Industries

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• Hospitals and Health Care
  

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