Software Engineer
3 weeks ago
Job Details
: General NotesMust be eligible to work in the United States on a full-time basis for any employer. Position expected to continue until March 1, 2027.
Deadline for Application: Applications will be reviewed continuously until the position is filled.
Contact Information: . Please note only applications through Workday will be considered. Purpose
Project Affiliation: Army Contract for AI-Driven Network Optimization
About the Project: This exciting opportunity at the University of Texas at Austin involves working on a cutting-edge AI networking project under the guidance of Professor Chandrajit Bajaj. The project focuses on developing Predictive Intelligent Networking (PIN) agents, employing advanced AI techniques for rapid response decision-making in predictive intelligent communication networks. Our innovative approach centers on enhancing network efficiency, reducing overhead traffic, automating PACE communications planning, and improving scalability in challenging environments. Our project is dedicated to crafting advanced machine-learning algorithms specifically designed for network optimization and security challenges. Through rigorous real-world simulation scenarios, we aim to deliver robust solutions that excel in environments with incomplete or uncertain data. This role offers the chance to be part of a pioneering effort to create generic solutions for heterogeneous Army networks, working within the confines of existing network protocols. What We Offer: A dynamic and collaborative research environment at the University of Texas at Austin. Opportunities to work on pioneering technologies in AI and network security. Access to state-of-the-art facilities and resources at the Computer Visualization Lab. A chance to contribute to a project with a significant impact in the field of C5ISR communications. UT Austin offers a competitive benefits package that includes: 100% employer-paid basic medical coverage Retirement contributions Paid vacation and sick time Paid holidays
Responsibilities
Develop AI agents focused on optimizing network topology for peak performance. Work collaboratively through various project stages, from conceptualizing theoretical frameworks to deploying practical solutions. Drive continuous enhancement of AI agent capabilities, focusing on PACE Routing, Load Balancing, and related features. Contribute to the production of detailed technical reports and presentations that showcase project progress and breakthroughs.
Required Qualifications
A strong foundation in AI/machine learning and software development. Experience with network simulation, optimization, and related technologies. Production experience with at least two programming languages Proficiency with tools pertinent to AI development and network engineering. Versatility in adapting to the dynamic needs and phases of an evolving, research-intensive project. At least 1 year experience in software development or system administration
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a closely related field. Demonstrable experience in an interdisciplinary team, preferably within a research or defense-focused environment. A solid understanding of communication protocols and experience in network analysis and data systems.
Salary Range
$84,000 + depending on qualifications
Working Conditions
Standard office conditions
Required Materials
Resume/CV
3 work references with their contact information; at least one reference should be from a supervisor Letter of interestImportant for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
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Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.----
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.----
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
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