"MDI Machine Learning Developer, Massive Data Institute - McCourt School of Public Policy"

Job Overview

The McCourt School of Public Policy at Georgetown University is a diverse community of problem-solvers, committed to moving bold ideas to action. We are global citizens, conducting policy-relevant research, and building bridges between our work and the communities we serve. The Massive Data Institute (MDI) at Georgetown's McCourt School of Public Policy harnesses modern data and computing power to produce cutting-edge social science, computer science, and data science research that improves public policy decision making.

The MDI Machine Learning Developer will engage in research, development, and implementation of machine learning models for health analytics projects, focusing on early detection of Alzheimer's using health and financial data, and building deep learning models to detect fake images, audio, and text. The MDI Machine Learning Developer will collaborate with researchers in McCourt, MDI, and the School of Health to develop and test different machine learning and dimensionality reduction approaches. The MDI Machine Learning Developer will focus on building and implementing classic and neural models for different application domains.

The MDI Machine Learning Developer will interact with researchers of various departments, schools, and other technical staff. This position reports directly to MDI Director Lisa Singh, and the MDI Technical Manager oversees the day-to-day activity of the technical team, including this position.

Requirements and Qualifications

• Undergraduate degree (BSc) in Computer Science.
• A minimum of 3 - 5 years of working experience in machine learning research and/or development.
• Strong technical skills, including experience with TensorFlow and/or PyTorch, API integration, and software development frameworks and pipelines.
• Experience with deep learning models and fine-tuning of generative models.
• The ability to develop new deep learning models, not just use existing ones.
• The ability to understand health research.
• Advanced programming and analytical skills.
• Understanding of statistics, statistical programming packages, and statistical modeling.
• Ability to design and code software independently.
• Skilled in the visual presentation of results.
• Ability to work collaboratively in a cross-functional team.

Preferred Qualifications

• Google (GCP), Amazon (AWS) or Azure Cloud experience.
• Programming proficiency in Java and Python.
• Proficient in deep learning models and frameworks, including PyTorch and TensorFlow.
• Application programming skills.
• Web development skills, including JavaScript, HTML, CSS.
• Database administration knowledge, PostgreSQL a plus.
• Prior experience with healthcare applications of machine learning.
• Prior experience with deepfake detection or computer vision and media analysis models.

Work Mode Designation

This position has been designated as Hybrid (3 days on campus/2 days telework).

Pay Range

The projected salary or hourly pay range for this position is: $66,783.00 - $126,720.23. Compensation is determined by a number of factors including, but not limited to, the candidate's individual qualifications, experience, education, skills, and certifications, as well as the University's business needs and external factors.

More details about Georgetown University's mode of work designations.