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

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

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.

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