Robotics and Autonomous System Designer Engineering Scientist

Robotics and Autonomous System Designer Engineering Scientist

Applied Research Laboratories – University of Texas at Austin

Position open to: All Applicants

Weekly scheduled hours: 40

FLSA status: Exempt

Earliest start date: Immediately

Position duration: Expected to continue

Location: PICKLE RESEARCH CAMPUS

As a Robotics and Autonomous System Designer you will design, implement, and test algorithms for autonomous decision‑making on Uncrewed Underwater Vehicles (UUVs) for the Advanced Technology Laboratory (ATL) at ARL.

• Identify, research, and develop autonomy algorithms that use sonar data to avoid obstacles, aid multi‑agent decision making, and dynamically replan current tasking and sorties.
• Design target recognition algorithms for locating objects in the environment and increasing situational awareness.
• Conduct data analysis across a range of acoustic systems, identifying anomalies and opportunities for improvement.
• Perform in‑water testing of generated algorithms, behaviours, and capabilities.
• Plan and coordinate field tests for algorithms in ocean, littoral, harbor, and riverine environments.
• Document work for knowledge transfer, consistency, and efficiency.
• Travel to support data collection, system evaluation, testing, and project meetings.
• Coordinate with project performers from other organizations.
• Develop system concepts and proposals and coordinate project execution with development staff.
• Perform other related functions as needed.

• Bachelor's degree in Robotics, Engineering, Computer Science, Mathematics, or other Applied Sciences.
• Three years of related experience.
• Demonstrated ability in the development and application of robotics, autonomy, or machine learning algorithms.
• Experience with implementation and testing of data processing algorithms.
• Proficiency in object‑oriented programming languages.
• Familiarity with MATLAB or Python and general programming languages such as C/C++ or Python.
• Familiarity with Unix/Linux operating systems.

• Advanced degree in Engineering, Mathematics, or Applied Sciences with emphasis in autonomous vehicles, robotics, learning systems, or data analysis.
• Three or more years of related experience.
• Cumulative GPA of 3.0 or higher.

Applicant must be highly organized, have excellent attention to detail, and possess sound scientific judgment. They must manage their own time and effectively plan, coordinate, and execute multiple tasks simultaneously. Regular and punctual attendance in the workplace is required.

US Citizen. Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to this position.

• 100% employer‑paid basic medical coverage
• Retirement contributions
• Paid vacation and sick time
• Paid holidays

$104,000 – $174,000+ (negotiable) depending on qualifications

• Standard office conditions
• Repetitive use of a keyboard at a workstation
• Use of manual dexterity
• Some weekend, evening, and holiday work
• Possible interstate/intrastate travel

• Resume/CV
• Three work references with contact information (at least one supervisor reference)
• Letter of interest
• Unofficial college transcripts

The University of Texas at Austin is an equal opportunity/affirmative action employer. It complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

The University of Texas at Austin will not discriminate against employees or applicants based on their own or others’ pay information. Employees who have access to compensation data as part of their essential job functions may not disclose such information except under specific circumstances defined by law or internal policy.