Machine Learning Engineer
GE HealthCare
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
DockerPythonPyTorch
About the role
- Lead small development teams, taking responsibility for the design, translating customer requirements into the product specifications.
- Develop ML models for a variety of clinical use cases.
- Including: Development of model training pipelines.
- Curation and construction of datasets suitable for model training.
- Prepare analysis on the performance of ML models, characterise their performance.
- Prepare technical documentation describing ML models, consistent with our quality management procedures.
- Work effectively with other members of the ML team and other cross-functional stakeholders in development projects, including clinical, regulatory, etc.
- Develop, support, and enhance prototypes and product concepts.
- Develop, support, and enhance internal tools and services for machine learning.
Requirements
- A 2.1 or 1st degree in a technical discipline, or an MSc or PhD in a relevant field.
- Some experience applying machine learning in a commercial setting or a PhD/MSc with a focus on machine learning.
- Excellent programming and software engineering skills, comfortable working with data in multiple formats, both structured and unstructured.
- Proficiency in Python (ideally PyTorch library) and using Docker containers.
- A good understanding of machine learning, and its use in solving complex real-world problems.
- Skilled in the use of Python for machine learning, and ideally using Pytorch.
- A solid understanding of image processing and analysis techniques for noisy data.
- A solid understanding of software engineering methodologies (e.g., version control, bug tracking, software development practices).
- The ability to comfortably work with large volumes of data.
- Experience in medical imaging, ideally ultrasound.
- Experience with development under ISO13485.
- 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.
- Demonstrable experience of taking design responsibility for ML developments.
Benefits
- Competitive salary
- Flexible working hours
- Professional development budget
- Home office setup allowance
- Global team events
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningmodel training pipelinesdataset curationperformance analysistechnical documentationprogrammingsoftware engineeringimage processingPythonPyTorch
Soft skills
interpersonal skillscommunication skillsself-starterteam playerorganizational skillsattention to detailcollaborationproactiveenthusiasmproblem-solving
Certifications
MScPhD