R&D Data Analysis and Machine Learning Software Engineer

University of Texas; Austin (TX); On-site; USD 104,000 - 174,000; Full time

Job summary

Applied Research Laboratories at UT Austin seeks an R&D Data Analysis and Machine Learning Software Engineer to advance data modeling, algorithm development, and software tooling for environmental science research.

The role blends research with software engineering: designing and testing algorithms, implementing in MATLAB and Python on UNIX/Linux, documenting results, and presenting findings to sponsors and internal groups.

Qualifications

• Bachelor’s degree in natural or engineering sciences including computer science/electrical engineering or related discipline.
• Three or more years of experience with data algorithms, ML methods, and applied research.
• Experience developing applications in MATLAB and Python in UNIX/Linux environments.

Responsibilities

• Design, develop, configure, apply, test, and support data analysis and machine learning algorithms.
• Design and write flexible software per designs and test to meet project requirements.
• Prepare technical documentation and present results at internal/external meetings.
• Communicate with team members, supervisors, and sponsors for timely implementation.
• Review peer software to improve designs and deployments.

Skills

Data analysis

Machine learning

Python

MATLAB

UNIX/Linux

C/C++

SQL

TensorFlow

Keras

Experimentation

Education

Bachelor's degree in natural or engineering sciences including computer science/electrical engineering

Master’s or Ph.D. in related discipline

Tools

MATLAB

Python

SQL

Git

Job description

## R&D Data Analysis and Machine Learning Software EngineerApplylocations: PICKLE RESEARCH CAMPUStime type: Full timeposted on: Posted Todayjob requisition id: R\_00047743**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:**## PurposeResearch 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 NotesAn 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$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**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.