Our team of part-time volunteers works with machine learning, deep learning, and signal analysis for audio analysis in a medical setting. We welcome individuals with professional experience in these domains to apply. The candidate will be immersed in a collaborative environment alongside AI engineers and mentors.

Responsibilities

• ●Deeply research and identify state-of-the-art ML approaches for detecting COVID from coughs.
• ●Train, build, and deploy AI models into production environments.
• ●Produce clean code and APIs to facilitate understanding within the team.
• ●Collaborate with product management and leadership to deliver on expectations.
• ●Build data ingest and data transformation infrastructure.
• ●Process and feature extract from a wide array of input data types.
• ●Identify transfer learning opportunities and auxiliary training datasets.
• ●Distill results into academic formats, e.g. research paper.

Requirements

• ●1-2 years of experience working in AI with at least 6 months in audio-processing.
• ●Passionate and committed to the Virufy mission, communicate effectively, and share learnings with the team.
• ●Strong Python programming experience with toolkits such as Pandas, NumPy, Librosa.
• ●Experience in training models with frameworks like Scikit-learn, Tensorflow, Pytorch, Keras.
• ●Experience in MLOPs
• ●Strong in Statistics
• ●Hands-on AI programming experience working on (ideally) enterprise products.
• ●Experience using AI for healthcare in clinical research studies and solving real-world problems.

Hours

• ●15-20 hours per week for a 6 month period

Questions?

• ●Reach out to frederick.cosper@virufy.org and we will get back to you promptly.

Virufy complies with the Immigration Reform and Control Act (IRAC). Virufy is an equal opportunity, volunteer-run, 501(c)(3) non-profit organization, and all qualified applicants will receive consideration for a volunteer opportunity without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by any applicable Federal, State, local, or international laws.