R&D Machine Learning Engineer, Engineering Scientist Associate

Job Posting Title:

R&D Machine Learning Engineer (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

Development of novel machine learning algorithms for application to sonar and underwater acoustics, as well as the accompanying data analysis to effectively characterize their performance in the Advanced Technology Laboratory (ATL).

Responsibilities

• Conduct data analysis across a range of acoustic systems, identifying anomalies and opportunities for improvement.
• Coordinate algorithm delivery to implementation and deployment teams.
• Identify, research, and develop algorithms to exploit information in various sensor systems
• Analyze and develop models of signal processing outputs to support system understanding
• Present results to research community
• Travel in support of data collection and system evaluation testing.
• Other related functions as assigned.

Required Qualifications

• Bachelor’s degree in physics, math, computer or information sciences, engineering, related technical area
• Demonstrated ability in Python or similar abstract language.
• Demonstrated knowledge in one or more of the following areas: machine learning, high-performance computing, data pipelining, applied statistics, robotics, Bayesian estimation, SLAM

Applicant must have a dynamic skill set, be willing to work with new technologies, be highly organized and capable of planning and coordinating multiple tasks. The position will require attention to detail, effective problem-solving skills and excellent judgment. Ability to work independently with sensitive and confidential information, maintain a professional demeanor, work as a team member without daily supervision and effectively communicate with all groups of clients. Able to work under pressure and accept supervision. Regular and punctual attendance.

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

• Advanced degree in physics, math, computer or information sciences, engineering, operations research, or related technical area.
• Two or more years of Python or C++ development
• Demonstrated knowledge in any of the following areas: distributed computing, embedded software development, data science, storage and database management, machine learning frameworks, and applied statistics
• Experience building and troubleshooting software systems
• Experience with scientific literature review
• Proven ability to work independently and take initiative.
• Eligibility for immediate access to classified information.
• 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

Please visit our Human Resources (HR) website to learn more about the total benefits offered.

Salary Range

$88,500-$120,000+/negotiable based on qualifications.

Working Conditions

• 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

Required Materials

• Resume/CV
• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest
• Unofficial college transcripts

Important 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