Research Software Engineer at jhu

Setup: Hybrid
Location: Cincinnati, Ohio
Level: not_specified

Description

The Johns Hopkins Data Science and AI Institute (DSAI) is seeking Research Software Engineers to design and develop software for advanced AI and data science applications. These engineers will collaborate with faculty on various projects, contributing to groundbreaking research in areas like AI/ML solutions, data analysis, and novel data science techniques. They will also focus on creating reusable software frameworks and translating recurring themes into sustainable scientific infrastructure.

Required Skills

Python
C++
AI/ML
deep learning
cloud computing
SQL
Linux OS
Git
test-driven development
continuous integration / continuous delivery
software containerization
RESTful web service principles and development
relational database principles and development
CUDA GPU programming
authoring open-source Python packages in PyPI

Additional Information

Required Previous Experiences: Three (3) year's experience working in software development in large projects
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 Qualifications: PhD in a quantitative discipline
Five (5) years’ experience as above in either AI/ML or data science concentration.
Experience developing, training, fine-tuning and applying LLMs and/or foundational models.
Experience deploying AI models onto clinical platforms.
Experience with large scale scientific simulations or simulations of air/terrestrial/sea vehicles.
Familiarity with data formats common in scientific domains such as medical imaging, genomic sequences, proteins, chemical structures, geospatial, oceanographic, and heath record data.
Experience in CUDA GPU programming.
Experience authoring open-source Python packages in PyPI.
Experience in open-source project governance.
Experience in open-source community adoption initiatives.