R&D Data Analysis and Machine Learning Software Engineer (Engineering Scientist Associate)

Job Posting Title:

R&D Data Analysis and Machine Learning Software Engineer (Engineering Scientist Associate) ----

Hiring Department:

Applied Research Laboratories ----

Position Open To:

All Applicants ----

Weekly Scheduled Hours:

40 ----

FLSA Status:

Exempt from FLSA ----

Earliest Start Date:

Immediately ----

Position Duration:

Expected to Continue ----

Location:

PICKLE RESEARCH CAMPUS ----

Job Details:

Purpose

Research and development for both data analysis and machine learning applications, including data modeling and algorithm development and implementation. Software design, development, and testing to support research and development efforts within the Environmental Sciences Laboratory (ESL) of Applied Research Laboratories.

Responsibilities

Design, develop, configure, apply, test, and support both data analysis and machine learning algorithms.

Designing and writing flexible and maintainable software according to software designs and test to ensure software meets project requirements.

Preparation of analysis presentations and technical reports.

Communicate with project team members, supervisors, and sponsors for timely implementation of project requirements.

Reviewing peer developed software to improve other developer's designs and implementations.

Deploying and supporting software outside of ARL.

Other related functions as assigned.

Required Qualifications

Bachelor’s degree in the natural or engineering sciences including computer science, electrical engineering, or related discipline.

Proficiency working with data algorithms (regression, probability, statistics).

Experience with machine learning algorithms and application libraries (Tensorflow, Keras, Theano, Torch, Infer.NET, or equivalent).

Demonstrated strong math background.

Experience developing applications in MATLAB or Python in a UNIX/Linux environment.

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 and managing their time. The position will require: attention to detail, effective problem-solving skills, sound engineering judgment, ability to work independently with sensitive and confidential information, ability to maintain a professional demeanor and work as a team member without daily supervision, and effectively communicate with various groups of clients; ability 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

Master’s degree or Ph. D. in the natural or engineering sciences including computer science, electrical engineering, or related discipline.

Advanced coursework or significant experience related to data analysis (statistics, pattern recognition, scalable machine learning, etc.).

Current or recent eligibility for access to classified information.

Two or more years of experience with one or more of the following:

Developing and evaluating data algorithms (regression, probability, statistics)

Machine learning algorithms and application libraries (Tensorflow, Keras, Theano, Torch, Infer.NET, or equivalent)

Experience working in an applied research environment.

Experience analyzing large, complex datasets using scalable techniques.

Experience with MATLAB MEX objects.

Experience with database integration and SQL programming.

Experience with C/C++.

Experience with signal processing algorithms.

Experience with scripting languages (Python, Shell).

Knowledge of version control systems or defect tracking systems.

Prior work experience in professional or research-oriented software development.

Proven ability to work independently, formulate research plans, take initiative, and mentor other staff.

Demonstrated excellent interpersonal communication and presentation skills.

Cumulative GPA of 3.0 or greater.

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 depending 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 Intrastate/interstate/international travel

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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 transcript

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

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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.

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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