R&D Machine Learning Engineer (Engineering Scientist Associate) Full-time

R&D Machine Learning Engineer (Engineering Scientist Associate)

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).

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.

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

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.

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

3 work references with their contact information; at least one reference should be from a supervisor

Letter of interest

Unofficial college transcripts

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.

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.