Lead Autonomy Software Engineer

About the Team:

The Sensors Division at STR focuses on technology development for advanced sensor systems and platforms in support of national security. We have a particular focus on airborne/surface/space-based radar, electronic warfare, underwater acoustics, hyperspectral imaging, and EO/IR sensing. We work on full system prototypes, experiment campaigns, and next generation technology components. Specific technical areas include RF analog/digital hardware, acoustic hardware, signal processing algorithms, machine learning algorithms, tracking/fusion, autonomous systems, as well as real-time embedded processor implementation.

The Systems Autonomy, Analysis, and Modeling (SAAM) Group within the Sensors Division uses modeling and simulation (M&S) to analyze system capabilities, develop enabling algorithms, and take these integrated systems through test. We focus on the capabilities and limitations of ground, air, surface, and space sensing and counter-sensing platforms and the resource management of these assets to assure the mission success of US air and space assets. SAAM also leverages the emerging use of autonomy and Artificial Intelligence in uncrewed systems and techniques to collect, fuse, and understand sensor data across full systems of systems to assure mission success. SAAM is developing software and hardware tools and datasets to support these analyses, including algorithms, processing chains, and scenarios to inform and deploy onto both prototype demonstration systems & operational systems. Our main customer focus is on Air Force, Navy, and DARPA research programs.

The Role:

As an Autonomy Software Engineer in the SAAM group, you will work as a part of high-performing teams focused on autonomy development and mission systems integration within demanding customer environments. You will ensure that these teams are executing at a high level to develop robust, fielded solutions that also lay the groundwork for future programs to build on.

What you will do:

• System Development: leverage mature hardware systems and develop code to integrate them together, collaborating with SMEs across STR to leverage advanced algorithms where needed

• System Test: work closely with test leads in the SAAM group to leverage testing capabilities across M&S and live test, leveraging Live-Virtual-Constructive (LVC) infrastructure

• Leadership: lead small, focused teams to implement and test real-time applications featuring open architecture software principles, implementing real-time systems in Modern C++ from verified algorithms written in higher-level languages such as MATLAB

• Customer engagement: support potential and current customer discussions to better understand their requirements and shape product development

Who you are:

• Self-motivated with demonstrated ability to excel under limited guidance

• Strong proficiency in modern C++ development, including multi-threaded applications

• Experience with test-driven development and CI/CD practices

• Familiarity with cross-platform development (Windows, Linux, iOS) and version control workflows

• Experience with hardware/software integration

• Minimum of 2 years relevant experience with PhD, 5 years with MS, or 7 years with BS

• Ability to obtain and maintain a secret security clearance, for which U.S citizenship is needed by the U.S government

Even Better:

• Active Secret or Top Secret security clearance

• 5+ years of C++ programming experience with open architecture systems

• Experience with safety-critical software architectures

• Experience with real-time software development and algorithm optimization

• Familiarity with network protocols and debugging

• Familiarity with relevant open standards such as OMS/UCI and A-GRA

• Experience with software quality tools (static/dynamic analysis, automated testing frameworks)

Pay Information Full-Time Salary Range: $174,000 - $225,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate’s experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.

STR is a growing technology company with locations near Boston, MA, Arlington, VA, near Dayton, OH, Melbourne, FL, and Carlsbad, CA. We specialize in advanced research and development for defense, intelligence, and national security in: cyber; next generation sensors, radar, sonar, communications, and electronic warfare; and artificial intelligence algorithms and analytics to make sense of the complexity that is exploding around us.

STR is committed to creating a collaborative learning environment that supports deep technical understanding and recognizes the contributions and achievements of all team members. Our work is challenging, and we go home at night knowing that we pushed the envelope of technology and made the world safer.

STR is not just any company. Our people, culture, and attitude along with their unique set of skills, experiences, and perspectives put us on a trajectory to change the world. We can't do it alone, though - we need fellow trailblazers. If you are one, join our team and help to keep our society safe! Visit us at www.str.us for more info.

STR is an equal opportunity employer. We are fully dedicated to hiring the most qualified candidate regardless of race, color, religion, sex (including gender identity, sexual orientation and pregnancy), marital status, national origin, age, veteran status, disability, genetic information or any other characteristic protected by federal, state or local laws.

If you need a reasonable accommodation for any portion of the employment process, email us at appassist@str.us and provide your contact info.

Pursuant to applicable federal law and regulations, positions at STR require employees to obtain national security clearances and satisfy the requirements for compliance with export control and other applicable laws.

Verified from the employer's public Greenhouse job collection. The provider-supplied title, description, location and application URL were normalized without inferring unstated facts.