Image Analysis AI/ML Engineer for Life Sciences

AI/ML Design, Development, and Verification Engineering for Image Processing for Life Sciences

Responsibilities: AI/ML Development and Validation Engineering:

Development tasks (but not limited to): (1) Code development (in Python at first, and later other languages) using existing frameworks (more than one, likely – e.g., Tensorflow, PyTorch, Keras); (2) Integrating with existing and newly available software for cryo-EM workflows (both opensource and commercial); (3) Analyzing performance and optimizing for the environments (with the use of tools from Intel and NVIDIA); (4) Implementing web and application user interfaces (Python, JavaScript, etc.)

Validation tasks: (1) Performing unit and system-level tests; (2) Verifying the consistency with various public datasets, working with beta customers for problem reproduction and root-cause

Software Engineering Discipline:  He/she will observe software development disciplines: (1) Code reviews and walk-throughs; (2) Incremental and full software generation; (3)  Software packaging; (4) Maintenance, version control; (5) Documentation; (6) Bug logging and tracking

Education and Experience: (1) The candidates will have a minimum of a B.S/B.A. in computer science and/or mathematics or a related field. Master’s degree candidates preferred.  Those pursuing graduate degrees will be considered as well; (2) Experience in code development and software release is essential. Should be familiar with Unix/Linux Operating Systems; (3) Should be familiar with AI/ML frameworks.  Should have experience and/or knowledge in neural network design, selection of hyper-parameters, and such techniques as Transfer Learning, Ensemble; (4) Experience in image analysis would be highly desirable; (5) Should be willing to provide code samples (preferably via a Github repository); (6) Good verbal and written communication skills are essential.