What are the responsibilities and job description for the Machine Learning Engineer - Computer Vision position at AngioInsight?
Company Description
AngioInsight provides an AI-driven solution for real-time, non-invasive assessment of stenosis and Fractional Flow Reserve (FFR) in cardiovascular care. Our technology offers rapid, accurate data on flow dynamics and anatomy, aiding in the detection of microvascular disease. With an automated workflow, AngioInsight ensures precision and reliability in cardiovascular diagnostics.
Job Description :
We are seeking a highly motivated and passionate Machine Learning Engineer to join our team. This is an exciting opportunity for individuals looking to apply their knowledge of machine learning in the medical field. As a Machine Learning Engineer, you will work closely with the Lead Engineer and a multidisciplinary team to develop and deploy machine learning models and pipelines, particularly for medical image processing tasks.
Key Responsibilities :
- Medical Image Processing
Assist in the design, development, and implementation of machine learning models specifically for medical image processing, under the guidance of the Lead Engineer.
Help prepare and preprocess large medical imaging datasets (e.g., X-ray coronary angiograms, CT coronary angiograms), including cleaning, transforming, managing labeling, and feature engineering.
Help evaluate model performance using appropriate and assist in optimizing for accuracy and efficiency.
Work with data scientists, software engineers, and cardiologists to integrate machine learning models into healthcare applications.
Stay updated on the latest developments in medical image processing, machine learning, and AI applications in healthcare, and apply these advancements to projects.
Report directly to the Lead Engineer, who will provide mentorship and oversee your development.
Required Skills and Qualifications :
Master’s degree in Computer Science, Electrical Engineering, Data Science, Biomedical Engineering, or a related field.
1-2 years of experience in machine learning or related fields, with a strong preference for industry experience in medical imaging. Internships, academic projects, and prior exposure to medical imaging are also highly regarded and will be considered.
Strong problem-solving skills and the ability to apply theoretical concepts to real-world medical applications.
Proven ability to work as a team player in a cross-disciplinary team, including healthcare professionals, with a strong willingness to contribute to collective goals and ensure successful project outcomes.