R&D Solutions Engineer; Transportation Simulation & Computer Vision

Description

Are you interested in shaping the future of transportation? Consider joining the Leidos team operating FHWA's Saxton Transportation Operations Laboratory (STOL), a USDOT research lab focused on the improvement of transportation operations, safety, mobility, and environmental impacts. STOL provides a variety of services to support the advancement and adoption of emerging technologies, including automation and communication in vehicles and on the roadside.

• The Leidos Surface Transportation group:  
• The Saxton Transportation Operations Laboratory: (Use the "Apply for this Job" box below)./STOL

Location: This role will be expected to work full-time at the customer site in McLean, VA

This position requires candidates be legally authorized to work in the United States without employer sponsorship AND be currently located in the United States for the current three consecutive years and be eligible for a Public Trust Clearance.

The R&D Solutions Engineer will be part of the Surface Transportation Group within Leidos, a nationally recognized leader in advancing transportation safety, operations, and innovation. The Surface Transportation Group partners with federal, state, and local agencies to deliver next‑generation solutions in intelligent transportation systems, connected and automated vehicles (CAVs), traffic operations, human factors research, and transportation safety. Leidos has played a central role in shaping the future of mobility, including developing national standards for infrastructure‑to‑vehicle communications, advancing traffic simulation and modeling, and supporting the U.S. Department of Transportation’s vision of zero roadway fatalities.

The position will work with external organizations—including state and local Departments of Transportation (DOTs)—to identify how computer vision technologies can improve transportation safety and operations and to create business development opportunities in these areas. The role focuses on connected and automated vehicle technologies, V2X deployments, advanced traffic management, and technology transfer. The successful candidate will combine strong principal investigator skills with technical depth in computer vision, stakeholder engagement, and simulation testing.

This position requires excellent communication skills, the ability to manage complex, multi‑stakeholder projects, and a passion for advancing transportation innovation.

• Develop and execute strategies for communications, outreach, and technology transfer.
• Lead stakeholder engagement across public, private, and research sectors by translating needs into actionable technical and programmatic requirements, and serve as a trusted liaison aligning research, deployment, and policy objectives.
• Serve as primary liaison with clients, partners, and stakeholders (DOTs, FHWA, MPOs, industry).
• Prepare and deliver high‑quality technical reports, presentations, and documentation; ensure risk identification, mitigation, and quality assurance across all deliverables.
• Support business development and technology transfer by contributing to proposals, advancing communities of practice, and transitioning research outputs into real‑world deployment and operational use.
• Execute innovative solutions involving the development and integration of ITS, CDA, and V2X/CV applications through the implementation of cutting‑edge and emerging technologies.
• Lead delivery of software and system engineering components that incorporate object recognition and automation for transportation applications, ensuring solutions meet both technical requirements and compliance standards.
• Serve as a technical lead on medium‑to‑large, complex projects in partnership with state and local Departments of Transportation (DOTs), providing oversight on design, development, and delivery.

• Master’s degree with 5+ years of relevant engineering experience; OR Bachelor's degree with 7+ years of experience in transportation technology.
• Several years of experience with object recognition and automation in the…