Software Engineer (No Security Clearance Required)

Etegent Technologies•Beavercreek, OH

3d•Hybrid

About The Position

Etegent Technologies is seeking a Software Engineer to transition data exploitation algorithms from research and development into usable software for Department of Defense and Intelligence Community customers. The role covers application software development from conceptualization and implementation through delivery and sustainment. It is based in the Dayton office, with some work performed at customer facilities. The immediate project focus includes signal processing, algorithm efficiency, web development, databases, infrastructure, and deployment. The position suits a curious, adaptable engineer who is comfortable learning new skills and working pragmatically on real-world challenges. The ideal candidate has experience across the software development lifecycle, attention to detail, and an interest in building software that enhances users’ capabilities. Experience supporting AFRL or NASIC on-site is preferred. The role also involves communicating development status and demonstrating software to customers, and may include monitoring project schedules, resources, and costs.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a computer-related engineering field.
Previous experience in Software Engineering; candidates may be new graduates or have varying levels of professional experience.
Experience with data visualization tools or libraries.
Knowledge and experience in object-oriented software development.
Knowledge and experience with unit-testing tools and methodologies.
Experience with the Linux operating system.
Strong oral and written communication skills.
Strong planning and capacity skills in a hands-on environment.
Ability to obtain and maintain a TS/SCI security clearance.

Nice To Haves

Master’s degree in Computer Science, Software Engineering, Data Science, or a related field.
At least 3 years of Software Engineering experience.
Experience with relational SQL databases, such as PostgreSQL.
Strong knowledge of Python and common data science and machine learning packages, such as NumPy and PyTorch.
Experience or knowledge in machine learning and machine learning pipelines.
Experience analyzing user requirements and translating them into technical designs.
Ability to understand requirements for designing or transitioning software into a production environment.
Ability to quickly become familiar with different algorithms.
Familiarity with geospatial standards, GIS applications, or geospatial data formats such as GeoJSON, KML, and Shapefiles.
Strong knowledge of C++, GPUs, and other embedded hardware.
Experience with web development and common frameworks such as React and TypeScript.
Knowledge and experience with WebGL, Web Map Service (WMS), and RESTful interfaces.
Experience with OpenGL, the QT framework, and Web Services.
Experience scaling algorithms for high-performance environments such as Cloud or DSRC.
TS security clearance with active SCI adjudication.
Experience working on-site to support AFRL or NASIC.

Responsibilities

Write efficient, modular, well-documented code.
Collaborate with machine learning scientists and engineers to build data analytics tools.
Develop customized tools to accelerate machine learning data curation and quality control, including machine-assisted data labeling and quality checks.
Develop reliable machine learning pipelines for research, training, evaluation, and deployment.
Build visualizations of complex numerical and scientific data.
Develop signal-processing chains and algorithms to process large sensor data volumes and make results available near real time.
Design and implement optimized, low-level code on embedded hardware.
Design and implement end-user applications that use machine learning algorithms.
Build and deploy machine learning and computer vision systems for analysts.
Architect user interfaces and APIs for sensor simulation, exploitation, and analytics.
Identify architectures and toolsets to support design implementations and optimize throughput.
Develop database schemas and application interfaces to scale solutions on high-performance computing and cloud environments.
Assist in monitoring and directing project schedules, resources, and costs.
Report software development status and demonstrate software to customers.
Build and maintain GitLab CI/CD pipelines for multiple projects.