Senior ML Research Engineer

Responsibilities

• Advise researchers in the design, planning, and implementation of software or data analysis that enriches research productivity and reliability.
• Build deep understanding of specific research activities through regular engagements.
• Develop a scope of work and timely project plan with regular milestones.
• Build and maintain software code and custom data processing pipelines for complex environments.
• Apply firm understanding of numerical methods or data analysis 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 stakeholders with project updates.
• Build internal code design and development guides for future contributors.
• Build advanced curriculum and teach workshops for researchers on sustainable software and data management practices that preserve the reproducibility of their research domain.
• Abide by and follow the Harvard University IT technical standards, policies, and Code of Conduct.

Skillset

• Minimum of seven years’ post-secondary education or relevant work experience.
• Expertise in implementing software engineering best practices such as code reviews, version control, documentation, and agile methodologies.
• Strong experience in machine learning/AI research and technical support.
• Deep understanding of modern machine learning architectures and optimization techniques.
• Proficiency in deep learning frameworks (PyTorch).
• Experience with Nvidia GPU stack and HPC technologies.
• Detail-oriented expertise, with strong problem-solving skills to support research.
• Excellent communication skills, able to simplify complex tech concepts.
• Strong team player with a service mindset, able to guide researchers.
• Proven track record of success in working in a cross-functional team in an agile environment.