Machine Learning Data Engineer - Obstetric Ultrasound
Remote, United Kingdom
GE HealthCare
GE HealthCare provides digital infrastructure, data analytics & decision support tools helps in diagnosis, treatment and monitoring of patientsGE 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. Together our Imaging, Ultrasound, Patient Care Solutions, and Pharmaceutical Diagnostics businesses help improve patient care from prevention and screening, to diagnosis, treatment, therapy, and monitoring. We are an $18 billion business with 51,000 employees working to create a world where healthcare has no limits.Job Description
Job Overview
The GE HealthCare Ultrasound business consists of ultrasound consoles, handheld ultrasound devices, and ultrasound IT solutions across 5 different 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. We aim to grow our offerings via organic as well as inorganic developments.
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 Knowledge/Skills/Abilities
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.
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.
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Additional InformationRelocation Assistance Provided: No
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Computer Science Data Analytics Deep Learning DICOM Docker Engineering ETL GCP Git GitLab Keras Kubernetes Machine Learning Mathematics Matplotlib MLOps Model training NumPy OpenCV Pandas Pharma PhD Physics Pipelines Python PyTorch Scikit-learn SciPy SQL Statistics TensorFlow
Perks/benefits: Career development Health care Transparency
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