At a Glance
- Tasks: Join us to configure databases and ML pipelines for ultrasound image interpretation.
- Company: GE HealthCare is a global leader in medical technology, dedicated to improving patient care.
- Benefits: Enjoy competitive salary, flexible work culture, and opportunities for career growth.
- Why this job: Be part of a team innovating AI solutions that enhance maternal health and patient outcomes.
- Qualifications: A degree in a technical field and experience with MLOps, Python, and cloud platforms required.
- Other info: This role is based in the UK; legal authorization to work is necessary.
The predicted salary is between 72000 - 100000 £ per year.
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.
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. 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.
#LI-MG1
Additional Information
Relocation Assistance Provided: No #J-18808-Ljbffr
Machine Learning Data Engineer - Obstetric Ultrasound employer: GE Healthcare
Contact Detail:
GE Healthcare Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Data Engineer - Obstetric Ultrasound
✨Tip Number 1
Familiarise yourself with AWS services, especially those related to database configuration and data transfer. Understanding how to efficiently manage cloud resources will set you apart from other candidates.
✨Tip Number 2
Brush up on your knowledge of MLOps practices, particularly around ETL pipelines and version control systems like Git. Being able to discuss these topics confidently during interviews can demonstrate your technical expertise.
✨Tip Number 3
Network with professionals in the medical imaging field, especially those working with ultrasound technologies. Engaging in relevant online communities or attending industry events can provide valuable insights and connections.
✨Tip Number 4
Stay updated on the latest advancements in machine learning frameworks and tools. Being knowledgeable about current trends can help you discuss innovative ideas during your interview, showcasing your passion for the field.
We think you need these skills to ace Machine Learning Data Engineer - Obstetric Ultrasound
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, medical imaging, and cloud infrastructure management. Use keywords from the job description to demonstrate that you meet the specific requirements.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about the role and how your skills align with the company's mission in healthcare technology. Mention any specific projects or experiences that relate to obstetric ultrasound.
Showcase Technical Skills: Clearly outline your technical skills, especially in Python, AWS, and MLOps practices. Provide examples of past projects where you've successfully implemented ETL pipelines or managed data in a cloud environment.
Highlight Team Collaboration: Since the role involves working with geographically distributed teams, emphasise your teamwork and communication skills. Share examples of how you've effectively collaborated on projects in the past.
How to prepare for a job interview at GE Healthcare
✨Showcase Your Technical Skills
Be prepared to discuss your experience with MLOps practices, ETL pipelines, and cloud platforms like AWS. Highlight specific projects where you've configured databases or managed data pipelines, as this will demonstrate your hands-on expertise.
✨Understand Medical Imaging
Familiarise yourself with ultrasound technology and medical imaging concepts. Being able to discuss relevant tools such as DICOM or OpenCV will show that you have a solid understanding of the field and can contribute effectively to the team.
✨Emphasise Team Collaboration
Since the role involves coordinating with multiple teams across different regions, be ready to share examples of how you've successfully collaborated in past projects. Highlight your communication skills and ability to work well in a team environment.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in real-world scenarios involving data management. Think of specific challenges you've faced and how you overcame them, particularly in a commercial setting.