Principal ML Research Engineer
Elucid
- Boston, MA
- Permanent
- Full-time
- Help build the data pipeline, including writing data curation algorithms and data loaders.
- Collaborate with clinical team members to ensure data quality and model validity.
- Create, test, and optimize deep learning models.
- Integrate deep learning models into a production environment.
- PhD in machine learning, computer science, mathematics, statistics or related quantitative field.
- 6+ years overall experience developing ML algorithms.
- 2+ years Python experience.
- At least 3 years of prior experience developing ML applications in industry, especially in the computer vision or biomedical image understanding (preferred) space. This work has resulted in publications, been integrated into product, or similar.
- Familiarity with Python-based deep learning frameworks (ideally PyTorch, but others ok too).
- Familiarity with modern MLOps tools like Weights & Biases, MLFlow, Neptune, etc.
- Familiarity with git and medium- to large-scale software development.
- Experience working in an FDA-regulated environment.
- Experience with optimization, e.g. Bayesian Optimization.
- AWS experience (EC2, S3, Sagemaker).
- C++ coding experience.
- Experience with VTK/ITK.
- Experience with Systems Biology models.