ProFound Therapeutics: Machine Learning Engineer

Unclassified - Boston, MA

Full-time - Entry Level

Boston, MA

About the position

ProFound Therapeutics is seeking a Machine Learning Engineer to expand its machine learning platform. As an early-stage biotechnology company, ProFound is working to revolutionize the human therapeutic landscape by discovering new human proteins and developing a unique dataset of their properties using a variety of computational and experimental tools. This dataset provides the ProFound machine learning platform with a powerful resource to create and test innovative machine learning methods, which have an immediate impact on the company's ability to develop new, first-in-class therapeutics. In this role, you will be responsible for understanding and implementing various machine learning approaches, including logistic regression, tree-based algorithms, causal and graph models, and neural networks. You will develop, train, and evaluate a wide variety of machine learning models using both in-house and external data. Successful models will be deployed into production and integrated closely with experimental platforms to create feedback loops. Collaboration with the machine learning and computational biology teams will be essential in this fast-paced environment that values rigor and independence. The position requires a combination of research and production-quality code development in a team setting, ensuring that all machine learning work is documented and reproducible. You will also be expected to communicate results effectively to computational biology and interdisciplinary audiences, contributing to the overall mission of ProFound Therapeutics.

Responsibilities

• Develop, train, and evaluate machine learning models to identify and prioritize novel therapeutic targets.
• Develop a combination of research and production-quality code in a team setting.
• Ensure machine learning work is documented and reproducible.
• Communicate results to computational biology and interdisciplinary audiences.

Requirements

• Bachelor's or master's degree in computer science, data science, or machine learning with 2+ years of industry experience, or a PhD in computational life sciences with research focused on machine learning.
• Expertise in Python and machine learning frameworks such as Scikit-Learn, Pytorch/Lightning, Optuna, and HuggingFace.
• Expertise in git version control and reproducible code.
• Proven experience developing, debugging, and applying a variety of machine learning models in cloud environments.
• Desire to work across a developing data stack, from data ingest to model deployment.
• Desire to work on biological problems and learn from domain experts.
• Energetic self-starter with the ability to work effectively in a startup environment.
• Excellent analytical, communication, and presentation skills.