R&D Machine Learning Engineer (Engineering Scientist Associate)

Job Posting Title :

R&D Machine Learning Engineer (Engineering Scientist Associate)

Hiring Department :

Applied Research Laboratories

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

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 thatALLRequired 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 questionspresented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.

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.

Equal Opportunity Employer :

The University of Texas at Austin, as an equal opportunity / affirmative action employer,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.

Pay Transparency :

The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.

Employment Eligibility Verification :

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.

E-Verify :

The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university's company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following :

Compliance :

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.