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

Pay
$88,500–120,000/yearAnnual period assumed — pay source
Salary Range $88,500-$120,000+/negotiable depending on qualifications Working Conditions
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

Work authorization
US citizens onlyUS 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

What you’ll work on

Full posting
  • Design, develop, and test data analysis and machine learning algorithms

  • Write flexible, maintainable software to project designs and requirements

  • Prepare analysis presentations and technical reports

  • Review peer-developed software and suggest design improvements

  • Deploy and support software outside of ARL

From the employer’s posting
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.
Reviewing peer developed software to improve other developer's designs and implementations.
Deploying and supporting software outside of ARL.

What you’ll bring

All qualifications

Core experience

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

Preferred experience

  • Experience working in an applied research environment.
  • 100% employer-paid basic medical coverage
  • Experience analyzing large, complex datasets using scalable techniques.
  • Experience with MATLAB MEX objects.
Qualification wording
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).
Experience developing applications in MATLAB or Python in a UNIX/Linux environment.
Experience working in an applied research environment.
100% employer-paid basic medical coverage
Experience analyzing large, complex datasets using scalable techniques.
Experience with MATLAB MEX objects.
Education & alternatives
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).
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.).
Apply at Utaustin

Posting record

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Status in our records
Live
First seen by us
Aug 13, 202684 days ago
Recorded sightings
171
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Lower than most similar jobs

$88.5K–$120K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 84

Up longer than most. Similar jobs usually come down between day 6 and day 70.

Well past Utaustin’s usual: its jobs come down by about day 21.

From 4,523 similar postings that came down, and 26 of Utaustin’s. Coming down is not always a hire.

Utaustin is hiring

11 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C
  • MATLAB
  • Python
  • SQL
  • Keras
  • TensorFlow
  • Theano
  • C++
Where the posting names them
- Experience with database integration and SQL programming. - Experience with C/C++. - Experience with signal processing algorithms.
- 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.
- Experience analyzing large, complex datasets using scalable techniques. - Experience with MATLAB MEX objects. - Experience with database integration and SQL programming.
- Experience with signal processing algorithms. - Experience with scripting languages (Python, Shell). - Knowledge of version control systems or defect tracking systems.
- Experience with MATLAB MEX objects. - Experience with database integration and SQL programming. - Experience with C/C++.
- 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.
- 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.

Your next step

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Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Job Posting Title:

R&D Data Analysis and Machine Learning Software 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 from FLSA

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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

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

​

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.

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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.

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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 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.

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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.

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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.

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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:

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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.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
Salary Range $88,500-$120,000+/negotiable depending on qualifications Working Conditions
Location & working pattern

Pickle Research Campus

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.
Work authorization
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
More source context
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] ----

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