Participate in the design of software that supports and enriches research productivity and reliability; implement software solutions. Develop software and data services with researchers to ensure that modern standards of reproducible code are kept.

Job Code

I1257P IT RC Software/Data Prof III

Job-Specific Responsibilities

The Nock Laboratory in the Department of Psychology at Harvard University is recruiting a Machine Learning Engineer (MLE) with expertise in machine learning (ML) and natural language processing (NLP). The MLE will work with a dynamic, multi-site team on a project aimed at improving identification of, and intervention on, mental health problems (e.g., suicide) using social media and other rich data sources. The MLE¿s primary responsibilities will be to design and develop ML models (with focus on NLP) using social media text data. The successful applicant will have strong programming skills, sufficient knowledge and technical expertise in ML and NLP to execute tasks independently, and interest in application of ML to the healthcare sector. Job duties include:

• Work with research team to design, develop, and implement ML/NLP models
• Assist in development of infrastructure for cleaning and processing data
• Run experiments to evaluate model performance, perform error analysis, and suggest and implement improvements
• Build, test, and debug pipelines for NLP components
• Assist with preparation of presentations and publications

Typical Core Duties

• Collaborate with researchers in the design, planning, and implementation software that enriches research productivity and reliability
• Build understanding of research activities through regular engagements
• Provide feedback on scope of work and project plan and track progress of regular milestones
• Build and maintain aspects of software code and custom data processing pipelines for complex environments
• Apply firm understanding of specific technology to develop custom solutions to meet researchers’ needs
• Work in a team of developers and researchers in collaboration with systems professionals
• Provide regular communications to project leads with updates
• Build internal code design and development guides for future contributors
• Teach workshops for researchers on sustainable software and data management practices
• Abide by and follow the Harvard University IT technical standards, policies and Code of Conduct

Requirements

#machine-learning