R&D Data Analysis and Machine Learning Software Engineer

University of Texas; United States; On-site; USD 104,000 - 174,000; Full time

Benefits offered by this job

Employer-paid medical coverage

Retirement contributions

Paid vacation and sick time

Paid holidays

Job summary

The University of Texas at Austin is seeking an R&D Data Analysis and Machine Learning Software Engineer for the Environmental Sciences Laboratory at Pickle Research Campus. You will develop and test data models and ML algorithms, and design software to support research activities.

Responsibilities include deploying software, documenting work, and presenting results to internal and external groups. Strong math, programming, and collaboration skills are essential.

Qualifications

• Bachelor’s degree in natural or engineering sciences including computer science, electrical engineering, or related discipline.
• 3+ years experience with data algorithms, ML algorithms and libraries (TensorFlow, Keras, Theano, Torch, Infer.NET).
• Experience in applied research environment; projects from conception to implementation.
• Demonstrated MATLAB and Python development in UNIX/Linux environments.

Responsibilities

• Design, develop, configure, apply, test, and support data analysis and ML algorithms.
• Write flexible, maintainable software to meet project requirements.
• Prepare technical documentation and presentations.

Skills

Data analysis

Machine learning

Python

MATLAB

UNIX/Linux

Documentation

Education

Bachelor's degree in natural or engineering sciences including CS/EE

Tools

TensorFlow

Keras

Theano

Torch

Infer.NET

SQL

MATLAB

Job description

Job Description

Job Posting Title: R&D Data Analysis and Machine Learning Software Engineer ---- 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.
• Prepare technical documentation and technical presentations.
• Presentation of analysis results at internal and external working group meetings.
• 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.
• Three or more years of experience and demonstrated proficiency 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) Demonstrated strong math background.
• Experience in an applied research environment, contributing to projects from conception to implementation.
• Experience developing applications in MATLAB and 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 varioius 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.
• Five 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 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.

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

Benefits

• 100% employer-paid basic medical coverage
• Retirement contributions
• Paid vacation and sick time
• Paid holidays
• Salary Range $104,000 - $174,000+/negotiable depending on qualifications.

Working Conditions

• Standard office conditions
• Repetitive use of a keyboard at a workstation
• Use of manual dexterity
• Possible 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 transcript

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: E-Verify Poster (English and Spanish) [PDF] Right to Work Poster (English) [PDF] Right to Work Poster (Spanish) [PDF]

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.

About Us

Start Here, Change the World At The University of Texas at Austin, tradition meets innovation in the heart of a city that frequents lists of the best places to live and work. Named by Forbes as one of America's Best Large Employers for the sixth year in a row in 2025, UT offers both a dynamic work environment and a gateway to vibrant local culture. Whether you're at the forefront of the student experience, conducting world-changing research or supporting the engine that drives Texas’ flagship university, working at UT means making a lasting impact on our city, our state and our world. Our more than 20,000 faculty and staff empower 55,000+ students to challenge ideas, pursue passions and shape their futures. Joining UT, you’ll become part of a community dedicated to making a meaningful impact on campus and throughout the world. Looking for a student job? Please see our Student Employment site.

Contact

Comments and Inquiries: Email comments to [e-mail]. For questions or concerns regarding equal opportunity only, contact Equal Opportunity Services. Additional information for applicants can be found on the Human Resources web page: Applying for Employment. For more job information, call the Human Resource Service Center at [phone], or toll-free at [phone]. UT Austin is a Tobacco-free Campus