Software Engineer

As a Software Engineer at Radiance Technologies, your primary responsibilities will involve researching, developing, and deploying machine learning algorithms applicable to both software and hardware. You will also be designing systems for optimization using scientific modeling, analyzing complex datasets to create high-performance software solutions, and collaborating with cross-functional teams to integrate modeling capabilities into DoD platforms.

To be successful as a Software Engineer at Radiance Technologies, you should possess strong programming skills in languages like C++ and Java, and understanding of Python or R scripting. Additionally, experience with modeling communications networks, full lifecycle software development, and familiarity with tools like Docker and Kubernetes is essential. A self-motivated attitude along with excellent organizational and communication abilities is highly valued in this role.

Radiance Technologies seeks candidates with proven experience in designing and developing software for constructive simulation systems. Full lifecycle software development experience is critical, covering areas from prototyping to deployment. Experience in specialized modeling and simulation tools like AFSIM, ITASE, and NGTS is also a plus.

Applicants for the Software Engineer position at Radiance Technologies are ideally required to hold a Bachelor's degree or higher in Computer Science, Computer Engineering, or a related field, with at least 30 semester hours in mathematics, statistics, and computer science. An active TS/SCI security clearance is also mandatory for this role.

Software Engineers at Radiance Technologies work in a dynamic and supportive environment that promotes innovation and collaboration. Being 100% employee-owned, the company nurtures a culture that encourages growth and development, ensuring that you can thrive as part of a multidisciplinary team dedicated to impactful defense solutions.

When answering this question, emphasize specific projects where you researched and deployed machine learning algorithms, particularly how they enhanced software functionality or performance. Discuss the algorithms you implemented, the challenges faced, and the outcomes of your work.

In your response, outline your methodology for system optimization, including any specific scientific and mathematical techniques you utilize. Mention how you analyze performance data to make informed adjustments that improve system efficiency.

To effectively answer this, detail your involvement in each stage of the software development lifecycle, from requirements gathering to deployment and maintenance. Use specific examples to illustrate challenges you overcame and how your contributions led to project success.

Discuss your proficiency in C++ and Java, providing examples of projects you've completed in these languages. Mention any additional languages you're familiar with, like Python or R, and explain how each language's features enhanced your work.

Illustrate your self-motivational techniques and organizational strategies that bolster your productivity when working independently. Provide examples of past experiences where you successfully completed tasks autonomously, showcasing your initiative.

Describe any past projects involving modeling and simulation tools like AFSIM, ITASE, or NGTS. Highlight the objectives of the projects and how you utilized these tools to achieve effective outcomes, especially in collaborative settings.

To answer this question effectively, discuss your understanding of DoD security policies and compliance practices in software development. Mention any experience you have with secure coding protocols and how they apply to your past roles.

Explain your strategies for professional development, including attending workshops, participating in industry forums, or pursuing certifications. Share how staying informed about emerging technologies has positively influenced your work.

Outline your analytical approach, mentioning tools and methods you commonly use to extract insights from large datasets. Provide an example of a previous project where you successfully interpreted data to drive software improvements.

Discuss your familiarity with Continuous Integration and Continuous Deployment (CI/CD) processes. Mention specific tools you’ve used, such as Jenkins or GitLab, and how implementing CI/CD practices improved your team's workflow and software quality.