Typical Day in the Role

Developing faster MRI scans and reducing radiation in CT scans to improve patient comfort and safety.
Creating infrastructure to stream signals from hospital instruments to the cloud for analysis.
Training AI models to predict patient conditions with less data, enhancing diagnostic accuracy and efficiency.
Refactoring code to run on large clusters, monitoring training jobs, and fixing issues as they arise.
Focusing on AI research, data wrangling, and software development to support these initiatives.

Candidate Requirements

Years of Experience Required: 5-7 years of experience in the field.
Degrees or certifications required: Ideal candidates should hold a Bachelor’s degree with 5 years of experience, or a Master’s or PhD degree with 2 years of experience. Familiarity with PyTorch (2 years of experience) and experience in designing, implementing, and debugging deep learning models is required. Formal deep learning training and experience in model parallelization are pluses.
Best vs. Average:
- Experience in medical imaging/terminology or biomedical fields.
- Medical engineering experience.
- AI expertise.
- Experience with medical imaging or biomedical fields to facilitate quicker onboarding and better communication.
- Familiarity with image reconstruction processes, which is a significant plus (MRI/CT/anything that needs to turn into images).
- Ability to collaborate effectively with researchers and other team members to achieve project goals.
- Strong problem-solving skills to address technical challenges in AI model training and data processing.
- Good communication skills to articulate technical details and project requirements clearly.
Performance Indicators: Performance will be assessed based on meeting deadlines and quality of work.

Top Skills Required

Minimum 2-3 years of experience with Python (writing machine learning software).
Minimum 2-3 years of experience with machine learning frameworks, particularly PyTorch.
Minimum 2-3 years of experience with VS Code (strong software development skills, including code refactoring, monitoring training jobs, and fixing issues).
Minimum 2-3 years of experience with GitHub and Azure.

Responsibilities

Implement deep learning models in the domain of medical imaging, image analysis, image reconstruction, and video processing.
Prepare and check datasets from raw instrument data, perform labeling, and assemble datasets.
Set up regression tests and work on model optimization for inference performance.
Train models on GPU clusters.
Undertake code refactoring to improve existing codebases.

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