Job Description Summary

Job Description

Job Summary:

The Machine Learning Engineer is responsible for developing, benchmarking, validating, and deploying a wide variety of deep neural network architectures for the purpose of extracting clinically-relevant knowledge from ultrasound images.

Location: Remote/work from home

Reports To: ML Engineering Manager

Duties/Responsibilities:

• Develop deep learning model training and testing pipelines to assess the performance on clinically-relevant image processing tasks.
• Organize data for labeling and annotation and subsequently integrate datasets into training pipelines as part of an iterative model improvement process.
• Keep up with literature on state-of-the-art deep learning techniques in order to implement the latest into our networks and pipelines.
• Develop machine-learning algorithms on a breadth of software frameworks (Keras, TensorFlow, PyTorch, scikit-learn).
• Contribute to deployment of models on a diversity of hardware platforms, including mobile devices.
• Read relevant medical literature to be able to develop sound validation procedures/metrics.
• Share theoretical and practical ideas in deep learning and machine learning with the rest of the team.
• Perform other duties as assigned.

Required Skills/Abilities:

• 5+ years of combined academic and/or industry experience in training, testing, developing, and analyzing deep neural networks (recurrent, convolutional, spatiotemporal, attention-based).
• Experience in developing and tuning custom neural network components such as layers and losses based on scientific literature.
• Deep theoretical and practical knowledge of machine learning principles and deep neural network techniques (separable and 3D convolutions, inference acceleration frameworks, network compression, adversarial training, etc.).
• Knowledge of computer vision and image processing techniques and methods.
• Experience with Python and the Python scientific stack (numpy, scipy, matplotlib, pandas, scikit-learn, scikit-image).
• Advanced experience with at least one major deep learning framework (Tensorflow, Keras, PyTorch, etc.).
• Experience with writing production code, testing frameworks, and code review process.
• Strong teamwork ethic, communication skills, and passion for learning.
• Proficient with Microsoft 365 or similar software.

Preferred qualifications:

• Knowledge of C++ in an industry context is a plus.
• Experience working with medical imaging data and familiarity with the DICOM data format.
• Publications in top-tier machine learning journals or conferences is a plus.

Supervisory Responsibilities:

• None

Education and Experience:

• Minimum bachelor’s degree (master’s or Ph.D. preferred) in Computer Science, Electrical/Biomedical Engineering, Physics, Neuroscience, Statistics, Mathematics, or related fields.

Additional Information