Junior Software Engineer DSP/Geolocation (Security-Cleared)

Rincon Research Corporation; Centennial (CO); On-site; USD 98,000 - 123,000; Full time

Benefits offered by this job

ESOP participation

401(k) plan with company contributions

Health and dental insurance

Disability insurance (STD/LTD)

Job summary

Rincon Research Corporation seeks a Jr. Software Engineer to design real-time cloud processing and DSP/geolocation solutions in a multidisciplinary R&D setting.

You will implement advanced algorithms, test with live data, and develop user interfaces and visualization tools to support front-line facilities. Emphasis on self-starting, adaptability, and ongoing learning in a security-sensitive environment.

Qualifications

• Degree (Bachelor's, Master's, or PhD) in Computer Engineering or Computer Science.
• Proficient in modern software engineering practices for testability and readability.
• Proficient in C++ and Python in Linux environments.
• Ability to obtain and maintain TS/SCI security clearance.
• US citizenship required.

Responsibilities

• Design real-time cloud processing solutions and geolocation algorithms.
• Develop and test software with real data for mission impact.
• Create effective user interfaces and data visualization tools.
• Stay current with tech trends and propose innovative solutions.
• Collaborate across systems engineering, development, and ops; self-start.

Skills

C++

Python

Linux

Cloud computing

Agile development

DevOps

TS/SCI clearance

US citizenship

Education

Bachelor's/Master's/PhD in Computer Engineering or Computer Science

Tools

Docker

Kubernetes

Git

REST API

CUDA

Shell scripting

REACT

Job description

Rincon Research Corporation seeks a Jr. Software Engineer to design real-time cloud processing and DSP/geolocation solutions in a multidisciplinary R&D setting.

You will implement advanced algorithms, test with live data, and develop user interfaces and visualization tools to support front-line facilities. Emphasis on self-starting, adaptability, and ongoing learning in a security-sensitive environment.