Title: Software Engineer: Machine Learning / Signal Processing
Location: Washington, DC or Culpeper, VA
Applied Research in Acoustics (ARiA) applies broad interdisciplinary expertise in acoustics, modeling & simulation, signal processing, and cognitive science toward innovative science and engineering research and development for a diverse set of government and corporate clients that focuses on modeling & simulation for training and model-based signal-processing and artificial intelligence for detection and classification. Partnering with government, industry, and academia, ARiA solves critical challenges.
To enable effective and efficient transition of applied research to advanced development of products and systems, ARiA is structured to bring together top-quality research scientists with development and software engineers in an environment in which research and development mutually benefit from joint leveraging of in-house expertise.
ARiA is a small business where you can make a big difference. Our employees, including those at entry-level, are working together with the CIO of the Air Force to use cognitive computing to change the way the government acquires technology and working with top Navy leaders to use video games and simulation to change the way sailors are trained to use sonar.
ARiA: Real Research. Real World.TM
For more information, visit www.ariacoustics.com.
ARiA is an Equal Opportunity Employer.
Software engineer to perform a variety of tasks including development and implementation of machine-learning algorithms and software, and design, development, and testing of machine-classification and cognitive systems, working in close coordination with ARiA scientists and engineers
Algorithm and software design, development, research, and testing to support prototypes and products
Supporting the transition of research algorithms to fielded prototypes
Preparing documentation to summarize design and status of prototypes and products
Assisting with in-field integration, testing, and support, with some local travel required
Using deep learning to understand the relevant physical features in acoustic scattering data for use in a project on remediating underwater sites contaminated by unexploded ordnance
Developing a cognitive tool that allows natural-language query of legal documents to answer user questions about government regulations
Developing an ontology-based expert system to suggest scenario designs for training and performing knowledge engineering to encode representations/models
Bachelor’s degree in Computer Science, Engineering, or equivalent
Knowledge of and experience with developing machine-learning applications/software (supervised and unsupervised learning, deep learning, kernel machines, latent semantic analysis, etc.)
Facility designing and developing code in standard languages (e.g., C, C++, Java, and Python)
Completion of at least one sizable software or systems engineering project, such as creating a machine-learning application or contributing to an open-source project
Exceptional ability and desire to acquire new knowledge and skills to solve challenges
Ability to work independently but collaboratively
Ability to manage multiple projects in a fast-paced professional office environment
Ability to communicate technical solutions to project management and the development team
Good oral and written communications skills
Applicants selected for employment will be subject to a government security investigation and must meet eligibility requirements, including U.S. citizenship, for access to sensitive information.
Desirable Skills, Qualifications, and Experience:
Experience with GPGPU programing (CUDA, OpenGL)
Knowledge of and experience developing knowledge-engineering or semantic-web applications
Experience with scientific computing (numerical integration, special functions)
Knowledge of and prior practical work in signal processing (linear-system theory, digital signal processing)
Exposure to signal processing applications in radar or sonar such as: beamforming, matched filtering, and spectral estimation
Knowledge of and facility with concepts from college-level physics (acoustics, wave propagation)
Knowledge of and facility with concepts from college-level mathematics (partial differential equations)
To apply submit resume/CV and cover letter with salary requirements to email@example.com.