Machine Learning Engineer

Harvard Medical School’s Core for Computational Biomedicine (CCB) is seeking a Machine Learning Engineer to lead the development and deployment of medical large language models.

Responsibilities

• Develop, implement, and optimize medical large language models for medical education and clinical decision support
• Collaborate with interdisciplinary teams including biologists, clinicians, and data scientists to translate domain requirements into computational solutions
• Monitor and apply advances in deep learning and machine learning to keep models state-of-the-art
• Build infrastructures for data transformation and data ingestion
• Create AI models that generate predictions from large-scale data
• Communicate the usefulness of AI models to non-technical stakeholders
• Transform machine learning models into APIs so other applications can interact with them
• Use expert knowledge to lead research AI and data science projects

Requirements

• Minimum of seven years post-secondary education or relevant work experience
• Master’s or PhD in Computer Science, Computational Biology, or a related field strongly preferred
• Minimum of 3 years hands-on experience developing complex deep learning solutions for scientific challenges
• Proficiency in the Python deep learning stack, including expertise with PyTorch, Numpy, and related packages
• Experience working with and processing large and diverse datasets, especially medical texts, journals, or electronic health records
• Ability to collaborate with non-technical stakeholders such as doctors and medical researchers
• Experience using experiment tracking and project management tools, including Weights & Biases
• Prior experience in fine-tuning large language models for specific tasks
• Demonstrated ability to optimize deep learning models for improved performance and efficiency
• Understanding of biology and/or medicine to connect machine learning to medical applications
• Track record of publications in technical conferences or journals

Technologies

• Python
• PyTorch
• Numpy
• Weights & Biases

Location & Work Format

• Boston, MA (hybrid)
• Standard schedule: 35 hours per week
• Some duties may be performed at a non-Harvard location as determined by unit leadership
• For hybrid employees not working at a Harvard location, work must be performed in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts
• When not working at a Harvard/Harvard-designated location, additional requirements may apply based on interview details
• Some visa types and funding sources may limit work location
• Individuals must meet work location sponsorship requirements prior to employment
• Interviews and onboarding are currently being conducted remotely and virtually

Additional Information

• Visa sponsorship: Harvard University is unable to provide visa sponsorship for this position
• Pre-employment screening: Identity, Education, Criminal
• Application status: Careers@Harvard portal
• Salary grade level: 060

Benefits

• Generous paid time off including parental leave
• Medical, dental, and vision 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