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Machine Learning Data Engineer - Obstetric Ultrasound

Ge Healthcare
Cardiff
1 week ago
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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.


Responsibilities

  • 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 to 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 Skills

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

Basic Qualifications

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

Eligibility Requirements

  • 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

  • Proactive team player who enjoys working independently
  • 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

  • Excellent interpersonal and communications skills (both written and verbal) with all levels of an organization; able to build good working relationships
  • Self-starter – requires minimal direction to accomplish goals, proactive and enthusiastic
  • Strong team player – collaborates well with others to solve problems and actively incorporates input from various sources
  • Exceptional organizational skills and attention to detail


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