Job Description

Position Description

About the Position:
The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics at Harvard Medical School is looking for a Machine Learning Engineer with expertise in developing large language models (LLMs) to advance CCB’s mission to leverage data and computation to transform research and education, and to improve health outcomes. CCB provides computational and analytic resources to advance scientific discovery within HMS through its multi-disciplinary team of computational and quantitative scientists who work on collaborative projects both within the center and with members of the HMS community. The selected candidate will play a pivotal role in advancing the center's mission to harness the power of computational techniques in the field of medicine. By developing medical LLMs, the engineer will contribute to educating the next generation of medical students and enhancing clinical decision-making processes.
Key Responsibilities:

• Develop, implement, and optimize medical large language models tailored to the needs of medical education and clinical decision support.
• Collaborate with interdisciplinary teams comprising biologists, clinicians, and data scientists to understand domain-specific requirements and translate them into computational solutions.
• Stay updated with the latest advancements in deep learning and machine learning to ensure the models developed are state-of-the-art.
• Develop infrastructures for data transformation and ingestion.
• Build AI models that make predictions based on large quantities of data.
• Explain the usefulness of the AI models created to stakeholders.
• Transform machine learning models into APIs to interact with other applications.

Basic Qualifications

• A Master's or PhD in Computer Science, Computational Biology, or a related field.
• Minimum of seven years’ post-secondary education or relevant work experience, education will count towards experience.
• Minimum of 3 years of hands-on experience in developing complex deep learning solutions to tackle scientific challenges.

Additional Qualifications and Skills

• Proficiency with the Python deep learning software stack, particularly expertise in PyTorch, Numpy, and related packages.
• Experience handling and processing large and diverse datasets, especially medical texts, journals, or electronic health records.
• Ability to collaborate effectively with non-technical stakeholders, such as doctors and medical researchers.
• Experience with experiment tracking and project management tools, notably frameworks like Weights & Biases.
• Prior experience in fine-tuning large language models for specific tasks.
• Demonstrated experience in optimizing deep learning models for better performance and efficiency.
• Understanding of biology and/or medicine to bridge the gap between pure machine learning and its applications in the medical field.
• A track record of publications in technical conferences or journals.

Additional Information

The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up-to-date on CDC-recommended vaccines.
Please note that we are currently conducting a majority of interviews and onboarding remotely and virtually. We appreciate your understanding.
The Harvard Medical School is not able to provide visa sponsorship for this position.
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Commitment to Equity, Diversity, Inclusion, and Belonging

We are committed to cultivating an inclusive workplace culture of faculty, staff, and students with diverse backgrounds, styles, abilities, and motivations. We appreciate and leverage the capabilities, insights, and ideas of all individuals. Harvard Medical School Mission and Community Values
https://hms.harvard.edu/about-hms/campus-culture/mission-community-values-diversity-statement

EEO Statement

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.

Harvard Medical School strives to cultivate an environment that promotes inclusiveness and collaboration among students, faculty and staff and to create new avenues for discussion that will advance our shared mission to improve the health of people throughout the world.