Embedded Software Engineer Co Op Jobs in Kankakee, IL

Details

This position is expected to attend meetings and be otherwise communicating during standard business hours

We are seeking a highly talented postdoctoral researcher  with experience and interest in state-of-the-art AI technologies, data science, and research software engineering, a. This position offers the opportunity to work in a world-renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting-edge AI-ready/agentic infrastructure for data and model discovery, model metadata extraction, and scholarly intelligence. The project will explore conceptual frameworks and system architecture to support data trust in the context of AI-enabled sience workflows. Experience and developing and deploying software is desired.
We are extending and maintaining the National Data Platform to support a new generation of discovery capabilities targeting AI-enabled (agentic) science workflows. . Building on ideas pioneered by the Democratizing Data 1 2 project ( insights.ndp.utah.edu ) , this project will explore approaches to discovery data and models that are trusted and fit for use by leveraging contextual information about their use derived from a range of sources including published literature. The approach includes extracting, linking, and presenting evidence from records to help users understand where models are used, how they are applied, what tasks they support, and how they evolve across scientific domains.
The successful candidate will contribute directly to the research and implementation of workflows for AI model identification, publication mining, metadata engineering, search and retrieval, and interactive user-facing systems. The role includes support for integration, development, deployment, maintenance, UI/UX, containerization, automation, and system-level optimization.
Please contact Jess Tate (jess@sci.utah.edu) for further information.
The SCI Institute:
The SCI Institute is a world-class research institute located within the new Warnock Engineering Building on the University of Utah campus. We are a highly dynamic, driven group of over 170 faculty, staff, and students. The overarching goals of the SCI Institute's scientific computing research are to create new techniques, tools, and systems, by which scientists may solve problems affecting various aspects of human life. We believe that to advance the state-of-the-art and create meaningful computational solutions for such complex systems, one needs to advance research in a number of areas within scientific computing, including: visualization, simulation, and modeling. The SCI Institute presents a highly challenging, collaborative work environment that can be deeply rewarding for the right individual. Further information is available at http://www.sci.utah.edu/.
Research Focus of This Position
This position centers on the design and development of systems that enable discovery and analysis of AI models used in scientific research publications. Rather than cataloging datasets cited by papers, this effort focuses on identifying and organizing information about:
AI models mentioned or used in publications
model families, versions, checkpoints, and architectures
tasks and scientific domains in which models are applied
evidence of reuse, benchmarking, fine-tuning, and comparison
links among papers, models, repositories, benchmarks, and supporting resources
search, ranking, and visualization interfaces for model-centric scholarly exploration
This work sits at the intersection of AI/NLP, scholarly knowledge extraction, software engineering, data infrastructure, and human-centered discovery systems.
Opportunities for Professional Development
Through the Cyberinfrastructure Professionals (CIP) Cooperative (Co-Op) at the SCI Institute, the successful candidate will access a strong community of research computing and data experts working together to support and sustain SCI's world-class research efforts. SCI's CIPs perform a wide range of advanced services that positively impact research outcomes, improve researcher productivity, and strengthen the growing SCI research enterprise. The Co-Op provides faculty and research staff with a stable environment for mentoring, growth, training, communication, and planning across diverse research projects. This role offers exceptional opportunities to:
contribute to high-impact interdisciplinary research
publish and present work in relevant venues
collaborate with experts in AI, data systems, and scientific computing
gain hands-on experience with production-grade research software and infrastructure
mentor students and junior developers
shape the future of AI-ready scholarly discovery platforms
Work Environment
You will contribute to cutting-edge computational methods for AI-ready model discovery, research knowledge extraction, and scientific search systems.
We offer:
flexible working hours
professional career development opportunities
collaboration with a multidisciplinary and research-driven team
access to strong computing and research infrastructure
a competitive benefits package through the University of Utah

Work with faculty, staff, and students in designing and developing computational tools in support of research projects.
Aid in the specification of software requirements in coordination with faculty or team leads.
Develop user interfaces, APIs with web front-end technologies like HTML5, SCSS, Vue, React, Typescript, D3.js, node.js, chart.js
Back end server component development with technologies such as Flask, Django, CKAN, ArangoDB, PostgreSQL, MongoDB, Redis, and Elasticsearch.
Create and maintain build, testing, and deployment systems with Git, Github, Slack, Docker, AWS, Circle-CI, webpack, npm and many others.
Develop high quality and well documented code.
Build CI/CD workflows to validate changes across multiple targets
Profile and optimize performance for data throughput and latency
Interface with collaboration partners and participate actively in a collaborative work environment to turn requirements into optimal solutions on a large scale.
Contribute actively to team discussions on architectural design and solutions by continuously looking for improvements.
Research and stay current with project-related scientific literature.
Identify and implement creative solutions to overcome problems.
Mentor postdocs, students, and junior software developers for best software practices.
Support the end-user community by responding to user questions posted on the discussion list, fixing bugs, and incorporating feature requests.
Help with the project website and discussion boards for user support, developer support, and announcements.
Contribute to teaching activities by preparing and presenting educational seminars

Postdoc

Applicants must demonstrate the potential ability to perform the essential functions of the job as outlined in the position description.

Strongly Preferred Skills:
Solid background and working knowledge of computer science fundamentals including algorithms, data structures, and object-oriented programming.
Experience with HTML and web technologies.
Good knowledge of server technology and databases.
Working with large codebases
Containerization (Docker) and building software for web deployment
Strong understanding of Linux toolchains and debugging tools
Debugging and critical thinking skills including identifying bottlenecks, and bugs and devising solutions to these problems.
Experience with GitHub Actions, GitLab CI, or similar CI/CD systems
PhD in Computer Science, Scientific Computing, Data Science, Informatics, AI/ML, or a closely related area, or equivalent research experience.
Preferred skills and experience:
Experience contributing to scientific computing frameworks
Knowledge of RDMA, libfabric, or similar low-level communication APIs
MCP and NLP integration
UI/UX design
Scientific visualization
CyberSecurity and AAI (OAuth2, Keycloak, etc)
Cloud deployment and Kubernetes
Non-Technical Skills
Able to work in a collaborative software development environment as well as working independently with minimal supervision and direction.
Able to learn new tools and technologies.
Being self-motivated and having good organizational, communication, and teamwork skills is essential.
Willingness and ability to collaborate in a highly diverse, multi-disciplinary environment.
Excellent oral and written communication skills necessary to effectively work in a multidisciplinary team environment.
Communication and presentation skills to engage technical and non-technical
audiences.
Strong interpersonal abilities and teamwork skills.
Highly motivated to support research projects.
Ability to manage time across simultaneous tasks.
Note: This job description is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

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