The Johns Hopkins Data Science and AI Institute (DSAI) is a new pan-institutional initiative at Johns Hopkins to advance artificial intelligence and its applications, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance.

DSAI seeks multiple Research Software Engineers with strong academic backgrounds and relevant experience in industry focused on designing and building state-of-the art AI models, data science techniques and applications of each to diverse domains. The successful candidates will work at the cutting edge of modern science in collaboration with DSAI affiliated faculty at Johns Hopkins University (JHU) on projects ranging from consulting and short-term service engagements to large, multiyear AI and data science initiatives and applications. DSAI will address the growing demand for high-quality professional software engineers within academia who can build dynamic, scalable, open software to facilitate accelerated scientific discovery across fields.

The DSAI engineers will be at the forefront of modern data intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability, and a dramatic increase in infrastructure, both in hardware and in personnel. JHU has long been a world leader in the broader domains of medicine and public health as well as a wide range of science and engineering fields. This combined with our ethos of building out capabilities to have demonstrable global impact (e.g., JHUs Coronavirus Resource Center the award-winning global resource for real-time data and analysis for COVID-19) and other unique large scientific data sets, like the archives for the Sloan Digital Sky Survey and several simulations, will be key leverage points that will make the DSAI successful.

Specific Duties & Responsibilities

• The successful candidates will participate 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.

• Projects may also involve analysis of massive data sets either in the cloud or on premises.

• They may require creation of novel data science techniques, software pipelines for processing of real-time high-frequency data processing workflows and may need the design of complex database models for storing and disseminating scientific data sets.

• Some projects may require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement.

• They may 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 the individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects.

Special Knowledge, Skills, & Abilities

• Expert-level knowledge of the Python programming language.

• Expert-level knowledge of multiple modern AI/ML, vision, NLP, bioinformatics and/or mathematical or computational libraries.

• Familiarity with or willingness to learn C++ or other languages may be needed.

• Familiarity with software containerization technologies such as Docker and Singularity.

• Familiarity with RESTful web service principles and development.

• Familiarity with SQL and relational database principles and development.

• Fluency in the Linux operating system and related tools.

• Familiarity with modern software engineering best practices, such as Git source control, peer code review, test-driven development, build automation and continuous integration / continuous delivery.

• Familiarity with cloud development and deployment.

• Demonstrated leadership and self-direction.

• Willingness to teach others both informally and in short course format.

• Willingness to continually learn new tools and techniques as needed.

• Excellent verbal and written communication.

Minimum Qualifications

• Masters in a quantitative discipline, e.g. computer science, engineering, astrophysics, bioinformatics with strong scientific computing and/or mathematics background.

• Three (3) years or more experience working in software development and/or data science in large projects in industry.

• This position does not allow for education or experience substitutions.

• Concentration and three (3) years’ experience in development and application of AI/ML or data science as described below.

• For AI/ML concentration, experience designing, developing, training and applying state-of-the-art AI/ML models and/or generative AI to practical applications such as vision, NLP, bioinformatics, chemical discovery, medical diagnostics, robotics, anomaly detection, recommendation systems and time series analysis.

• For data science concentration, experience designing, developing and applying state-of-the-art data science techniques to the analysis of large data sets. Areas of relevant expertise include design and development of statistical and mathematical models of data, data transformation, ETL and information extraction, data modeling of complex scientific datasets, architectures for computing with large datasets, distributed computational pipelines and real-time data streaming architectures.

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.

Classified Title: Scientific Software Engineer

Job Posting Title (Working Title): Research Software Engineer

Role/Level/Range: APPTSTAF/01/ST

Starting Salary Range: Commensurate with experience

Employee group: Full Time

Schedule: 37.5 hrs/wk, M-F

Exempt Status: No SAP Value

Location: Hybrid/Homewood Campus

Department name: ​​​​​​​AI-X

Personnel area: Whiting School of Engineering

Equal Opportunity Employer:

Johns Hopkins University is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria. The university promotes affirmative action for minorities, women, disabled persons, and veterans.