Machine Learning Engineer

Harvard University • Boston, MA

58d • Hybrid

About The Position

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a Machine Learning Engineer with advanced expertise to lead development of 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.

Requirements

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

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.
• Use expert knowledge to lead research AI and data science projects.

Benefits

• Generous paid time off including parental leave
• Medical, dental, and vision health insurance coverage starting on day one
• Retirement plans with university contributions
• Wellbeing and mental health resources
• Support for families and caregivers
• Professional development opportunities including tuition assistance and reimbursement
• Commuter benefits, discounts and campus perks

What This Job Offers

• Job Type: Full-time
• Career Level: Senior