Harvard University is hiring a Full-Stack Machine Learning Engineer

Harvard University is hiring a Full-Stack Machine Learning Engineer to join a research lab in the Department of Psychology focused on studying suicidal thoughts and behaviors. You will manage, analyze, and visualize behavioral and clinical data streams to advance the understanding, prediction, and treatment of this critical public health issue.

What You'll Do

• Work with researchers to support the design, development, and implementation of ML models.
• Build and maintain infrastructure for cleaning, processing, analyzing, and visualizing diverse data types like GPS, accelerometer, and digital phenotyping data.
• Run experiments to evaluate model performance, conduct error analysis, and implement improvements.
• Conduct higher-level data analysis and supervise analyses performed by other lab members.
• Integrate data across workflows, including digital phenotyping, behavioral, and clinical data.
• Help develop and support a secure, scalable dashboard or lightweight clinical app for real-time data synthesis and visualization.
• Deploy modular, reusable visualization components and maintain version-controlled code repositories.
• Collaborate with university and Harvard teaching hospital IT teams to ensure interoperability, reliability, and clinical relevance.
• Assist with preparing grant applications, presentations, and publications.

What We're Looking For

• A minimum of five years’ post-secondary education or relevant work experience.
• 3-5+ years of hands-on experience with time-series, sensor, or biomedical/wearable data.
• Proficiency in Python and/or JavaScript, with libraries for ML (TensorFlow, PyTorch), data engineering (pandas, NumPy), and visualization (Plotly, Dash, Bokeh).
• Experience deploying dashboards or apps using tools like Dash, Streamlit, React, or Flask.
• Experience building real-time or streaming data pipelines.
• Expert-level knowledge of statistical programming, particularly R (tidyverse, ggplot2) and R Markdown.
• Strong understanding of ML approaches for classification, anomaly detection, and prediction using high-frequency data.
• Experience with multilevel longitudinal data, missing data strategies, and clinical outcome modeling.
• Experience with EHR data, REDCap, Qualtrics, or hospital-based informatics systems.

Nice to Have

• Completion of Harvard IT Academy specified foundational courses (or external equivalent).

Technical Stack

• Languages: Python, JavaScript, R
• ML Frameworks: TensorFlow, PyTorch
• Data & Visualization: pandas, NumPy, Plotly, Dash, Bokeh, tidyverse, ggplot2, R Markdown
• App Frameworks: Dash, Streamlit, React, Flask

Team & Environment

You will join a dynamic, multi-site team working at the intersection of machine learning, digital phenotyping, pediatric mental health, and real-time clinical decision support.

Benefits & Compensation

• 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
• Compensation aligns with Salary Grade 057 (see Harvard's Salary Ranges)

Work Mode

This is a hybrid role. Candidates must be able to work from a Harvard registered state.

Harvard University is dedicated to creating a diverse and welcoming environment where everyone can thrive. We foster ambition, curiosity, and a shared commitment to knowledge. Harvard University is an equal opportunity employer, prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law.