Lead Software Engineer

STR•Arlington, TX

7d•Onsite

About The Position

STR's Intelligence Division researches and develops advanced analytics and software solutions to solve challenging problems relevant to national security. Our team specializes in applying cutting-edge machine learning and computer vision in areas such as biometrics, target recognition and autonomous agents to solve national security and intelligence problems. We tackle complex technical challenges under stringent operational constraints by leveraging diverse skill sets from fields such as engineering, computer science, and applied machine learning. Our projects focus on a wide range of data modalities—including biometric data, video imagery, geospatial, and radio-frequency data—powered by the latest advances in deep learning and statistical techniques. Our solutions have real-world impact, allowing U.S. Government analysts and operators to extract and enrich intelligence information across the globe. If you’re motivated by making a difference while working in a collaborative and fast-paced environment and have experience with systems integration, robust application development, and messaging pipelines, we’d like to hear from you.

Requirements

BS Degree in a scientific field such as Computer Science, Mathematics, Statistics, Data Science, or Physics with 8+ years of relevant experience. Equivalent experience will be considered.
Ability to obtain a security clearance, for which U.S citizenship is needed by the U.S government

Nice To Haves

Development experience with advanced messaging or real-time processing tools like RabbitMQ, Kafka, or ZeroMQ
Experience with integration of computer vision algorithms and image processing tools (e.g., Pytorch, OpenCV, ffmpeg)
Experienced in leading and directing research initiatives from inception to functional prototypes
Experience working in a large cross-functional, distributed team
Experience with US Government software accreditation processes
Active security clearance

Responsibilities

Translate stakeholder requirements into system features and components in a deployable AI/ML solutions stack
Develop new user-facing features and implement robust backend architectures to support them.
Build, maintain, and test messaging systems, such as real-time data workflows and distributed processing pipelines.
Optimize software for data ingestion, transformation, and intelligent storage/retrieval pipelines.
Maintain and improve workflows for distributed systems, ensuring reliability and performance testing in operational environments.
Participate in cross-program collaboration, adapting to diverse projects and tools.