SCCI is currently seeking a Senior Software Developer to join our team! In this position you will work in a newly established R&D department focused on delivering next-generation autonomous systems and immersive training solutions for defense and government customers. This role demands deep expertise in applied machine learning, with a direct hand in prototyping and fielding AI-driven capabilities that address real operational requirements. The ideal candidate brings a proven track record of translating complex ML concepts into working systems within the constraints of defense hardware, software, and security environments. If you are motivated by mission-critical impact and the challenge of building at the edge of what is possible, we want to hear from you! This position is located in Dahlgren, VA.
SCCI offers a comprehensive and competitive benefits package including Health, Dental, Vision, Life and Disability benefits, 401k with Company Match, time off consisting of 2 weeks of paid vacation, 48 hours of sick/personal leave, and 11 paid Holidays.
Proactively identifies emerging DoD capability gaps and operational needs, developing AI/ML prototype concepts in advance of formal government solicitations to position SCCI for OTA responses, SBIR/STTR opportunities, and DoD challenge competitions
Drives the R&D technical vision for AI/ML capabilities, with a current focus on computer vision, edge-based inference, and autonomous swarm control while continuously scanning the threat and technology landscape to anticipate the next competitive frontier
Translates operational military requirements into prototype AI/ML solutions that are demonstrable, defensible, and transition-ready for program of record or follow-on acquisition
Collaborates with Program Manager to document technical project objectives, effort estimates, and milestone schedules for AI/ML R&D efforts and tracking execution against plan
Designs, develops, and iterates AI/ML prototype solutions with emphasis on computer vision applications for edge-deployed systems
Develops and optimizes models for deployment on resource-constrained edge hardware, balancing inference performance, power envelope, and operational reliability
Integrates AI/ML capabilities into simulation and training environments to produce adaptive, hyper-realistic training scenarios that respond dynamically to trainee behavior and mission context
Maintains a working prototype pipeline that enables rapid demonstration to government customers, OTA consortia, and DoD evaluators with minimal lead time
Identifies and escalates technical risks early, proposes mitigation approaches, and adjusts development priorities to keep prototype efforts on schedule and within resource constraints
Mentors and technically guides junior and mid-level developers in applied AI/ML concepts, development practices, and defense problem framing — building internal depth in a skill area where bench strength is currently limited
Establishes repeatable development patterns, coding standards, and documentation practices that enable the broader team to contribute meaningfully to AI/ML prototype efforts over time
Actively monitors competitor capabilities, government R&D investment trends, and emerging academic and commercial AI/ML advances to ensure SCCI maintains a differentiated and defensible position in the autonomous systems and simulation training marketspace
Contributes technical concepts for white papers, capability briefs, technical volumes, and proposal content that articulate SCCI’s AI/ML vision and prototype achievements to government customers and industry partners
Must be a U.S. Citizen and have an active Secret Security Clearance
Bachelor of Science (BS) degree in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related technical field required
Five (5) - Seven (7) years of hands-on applied AI/ML development with a portfolio of prototype or fielded systems demonstrating end-to-end ownership from concept through demonstration
Demonstrated expertise in computer vision development and deployment, including object detection, tracking, classification, and scene understanding in operationally relevant contexts
Proven experience deploying AI/ML models to edge hardware under real-world constraints of limited compute, power, bandwidth, and connectivity with demonstrated optimization techniques (quantization, pruning, distillation, or equivalent)
Demonstrated experience developing AI/ML solutions that implement human-machine teaming principles reducing operator cognitive load in high-tempo, data-rich operational environments through intelligent automation, prioritized cueing, and adaptive interface behavior and maintaining human-on-the-loop or human-in-the-loop control consistent with DoD AI ethics and autonomy policy
Demonstrated track record of delivering working prototypes on compressed timelines without detailed requirements, translating ambiguous operational problems into functional, demonstrable AI/ML solutions
Demonstrated ability to own a technical effort completely from planning, execution, risk management, through delivery with minimal oversight
Demonstrated experience defining technical project objectives, estimating work effort and milestone schedules while holding themselves and their team accountable to delivery without external management pressure
Demonstrated experience mentoring and technically leveling up junior and mid-level developers in applied AI/ML, producing measurable growth in team capability over time
Proven ability to establish development standards, reusable patterns, and documentation practices that extend their own impact across a small team
Experience working within DoD, defense contractor, or government R&D environments with familiarity of military operational contexts, acquisition frameworks, and transition pathways
Demonstrated experience presenting prototype capabilities and technical concepts to government customers, OTA consortia, program offices, or at defense industry events
Proficiency with Atlassian suite, Google Workspace, and Microsoft Office tools for project tracking, documentation, and cross-functional collaboration
Demonstrated use of AI-assisted development tools to accelerate R&D workflows and prototype velocity
Demonstrated experience identifying, evaluating, and recommending compute and hardware infrastructure for AI/ML development and testing environments, including edge devices, GPUs, and supporting lab equipment
