R&D Software Engineering Scientist Associate

Job Posting Title:

R&D Software Engineering Scientist Associate

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Hiring Department:

Applied Research Laboratories

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

40

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FLSA Status:

Exempt

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Earliest Start Date:

Immediately

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Position Duration:

Expected to Continue

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Location:

PICKLE RESEARCH CAMPUS

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Job Details:

Purpose

The Signal and Information Sciences Laboratory (SISL) is seeking a motivated individual to support the development, testing, implementation, and deployment of software to support geospatial data analysis and remote sensing applications.

Responsibilities

• Designing software applications and algorithms to support remote sensing, geospatial data analysis, and data science applications.

• Conducting software testing, code reviews, CI/CD, and verification to support development operations (DevOps).

• Writing flexible and maintainable software code according to software best practices.

• Developing, training, testing, and deploying Machine Learning (ML) solutions to support project requirements.

• Improving legacy software code to meet new project requirements.

• Reviewing peer-developed software to improve team designs and implementations.

• Deploying and supporting software delivered to sponsors outside of ARL:UT.

• Other related functions as assigned.

Required Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or other related discipline.

• Experience using Python for algorithm development, data science, and/or machine learning.

• Experience using JavaScript for front-end web development and visual data analysis.

• Familiar with the software development process to design, develop, and maintain software.

• Knowledgeable using tools to perform testing, version control, and documentation of code.

• Experience developing on Linux and Windows operating systems.

• Demonstrated ability to work effectively, both independently and collaboratively, with a strong commitment to contribution and enabling the entire team.

Applicant must be highly organized, have excellent attention to detail, and possess sound scientific judgment.  The position will require effective management of their own time with the ability to 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 the project requirements of the position.

Preferred Qualifications

• Master’s degree in Computer Science, Computer Engineering, or other related discipline.

• Experience using Python to develop and implement ML and Deep Learning model architectures.

• Developing applications for geospatial data analysis

• Developing applications for computer vision.

• Experience using C++ to develop and run software applications.

• Experience using GPU-accelerated ML and related frameworks.

• Experience with Docker or other containerized application development platform

• Three or more years of experience working in a computer science or data science field.

• Cumulative GPA of 3.0.

General Notes

An agency designated by the federal government handles the investigation as to the requirement for eligibility for access to classified information. Factors considered during this investigation include but are not limited to allegiance to the United States, foreign influence, foreign preference, criminal conduct, security violations, drug involvement, the likelihood of continuation of such conduct, etc.

Please mark "yes" on the application question that asks if additional materials are required.  Failure to attach all additional materials listed below may result in a delay in application processing.

Visit our website (www.arlut.utexas.edu) for additional information about Applied Research Laboratories.

UT Austin offers a competitive benefits package that includes:  
·    100% employer-paid basic medical coverage 
·    Retirement contributions  
·    Paid vacation and sick time 
·    Paid holidays 
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