
11 - 50 employees
📚 Education
🤖 Artificial Intelligence
🏥 Healthcare
Education • Artificial Intelligence • Healthcare
JHU EEHPC is the Energy Efficient High Performance Computing Lab at Johns Hopkins University, led by Tinoosh Mohsenin. The lab focuses on designing medical, health, and wearable devices and developing tiny, energy-efficient wearable and mobile computing systems through cross-layer approaches spanning algorithms, architecture, hardware, and system integration. It applies high-performance computing and artificial intelligence methods to smart health monitoring, robotics, autonomous navigation, and related domains, aiming to revolutionize healthcare, transportation, and public utilities.
🔥 12 hours ago
Where this job comes from
Posted on JHU EEHPC's careers page, not through a job board
First seen by Remote Rocketship 12 hours ago
Still open on JHU EEHPC's site. Checked 59 minutes ago.

11 - 50 employees
📚 Education
🤖 Artificial Intelligence
🏥 Healthcare
Education • Artificial Intelligence • Healthcare
JHU EEHPC is the Energy Efficient High Performance Computing Lab at Johns Hopkins University, led by Tinoosh Mohsenin. The lab focuses on designing medical, health, and wearable devices and developing tiny, energy-efficient wearable and mobile computing systems through cross-layer approaches spanning algorithms, architecture, hardware, and system integration. It applies high-performance computing and artificial intelligence methods to smart health monitoring, robotics, autonomous navigation, and related domains, aiming to revolutionize healthcare, transportation, and public utilities.
• Continue development of AI-powered data tools for early intervention programs • Own the application end to end, including data processing, user interface, AI capabilities, and evaluation • Build and maintain an interactive dashboard for Part C teams to explore Child Outcomes Summary data • Provide data-grounded guidance using national technical assistance resources • Define complex business, clinical, and education problems through client meetings and process observation • Gather and document complex system requirements • Develop project plans, functional and technical specifications, data structures, transformations, algorithms, and outputs • Design, build, maintain, and document an AI-powered data application • Develop generative AI features using retrieval-augmented generation over authoritative domain sources • Establish quantitative and expert-review evaluation processes for AI outputs • Protect sensitive personally identifiable information and ensure responsible, cost-effective AI use • Create and execute complex test scenarios; validate application functionality and error handling • Implement changes under change-management procedures • Monitor applications, resolve complex problems, and provide production support • Collaborate with the Frontend UX Engineer and domain experts • Provide technical guidance and mentorship to junior staff • Author technical and end-user documentation
• Bachelor's Degree (or foreign equivalent) in computer science, computer information systems, information technology, electronic engineering, or a related field • Five years of related work experience with computer systems and applications • Additional education may substitute for required experience; additional related experience may substitute for required education beyond HS Diploma/Graduation Equivalent, subject to the JHU equivalency formula • Knowledge of the assigned application and its platform • Experience with data-driven applications, preferably in Python • Experience building retrieval-augmented generation (RAG) systems, vector databases, knowledge graphs, and retrieval evaluation • Experience designing LLM-powered features, prompt engineering, and tool-using agents • Experience building and deploying web applications, including React and serverless functions • Experience evaluating AI systems using quantitative measures and human review • Understanding of privacy and security practices for sensitive data • Portfolio demonstrating AI systems built and evaluated • Experience with client-side data processing, document retrieval preparation, and education or public-sector data • Intermediate proficiency in Agile Methodology, algorithms, APIs, CI/CD, cloud serverless computing, code review, data architecture and design, data structures, debugging, DevOps, JIRA, new product development, secure coding, service-oriented architecture, software design patterns, SDLC, software engineering, and unit testing • Successful candidates subject to a pre-employment background check • Johns Hopkins faculty, staff, and students must receive the seasonal flu vaccine, subject to exceptions
• Total rewards package supporting health, life, career, and retirement • Seasonal flu vaccine, with religious or medical exceptions • Pre-employment accommodations and accessibility support • Required vaccinations for applicable positions provided at no cost • Remote work arrangement
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