Research Software Engineer - Robotics & Simulation (Data Science and AI Institute)

Job summary

Affiliated Office Address Baltimore, MD, United States Requisition ID 121856 Date Created July 16, 2026 Job Function Research Exempt Status Exempt Shift Type Full Time Schedule M-F, 37.

Benefits

Qualifications

• Masters in a quantitative discipline, such as Computer Science, Engineering, Physics or Bioinformatics with strong scientific computing and/or mathematics background
• Three (3) years experience working in software development and in large projects and three (3) year's experience in development and application of,
• AI/ML - developing, training and applying state of the art models in practical scientific applications aligned with DSAI domains, or
• Data science - modeling, transforming, applying ETL pipelines, and similar operations to complex data sets at scale.
• Preferred
• PhD in a quantitative discipline (highly preferred).
• Exceptional ML
• Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement.
• More information can be found here: https://hr.jhu.edu/
• but are completing their final academic semester/quarter will be considered eligible for employment and may be asked to provide additional information confirming their academic completion date.
• Background Checks
• The successful candidate(s) for this position will be subject to a pre-employment background check.

Responsibilities

• Work collaboratively in a team with other RSEs and scientists.
• Participates in ground-breaking research projects that need advanced software solutions requiring expertise in software engineering not commonly found in scientific collaborations.
• The projects may
• Require the creation of AI/ML solutions using the latest deep learning libraries trained on state-of-the-art hardware.
• Involve analysis of massive data sets either in the cloud or on premises.
• Require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement.
• Require software solutions developed from scratch or refactoring existing solutions to make them conform to industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.).
• It is a high-level goal of DSAI to translate the efforts for individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects.
• Develop software to implement novel scientific research algorithms.
• Create and run data processing workflows utilizing on-premise or cloud-based.
• computing infrastructure.
• Develop data models.

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Degrees

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