Transportation Engineer

Description

Are you interested in improving and shaping the transportation industry with a group of intelligent and motivated individuals? Consider joining the Leidos team operating the Federal Highway Administration (FHWA)’s Saxton Transportation Operations Laboratory (STOL), a USDOT research lab focused on the improvement of transportation operations, safety, mobility, and environmental impacts. STOL champions the integration of emerging technologies such as cooperative driving automation (CDA) and Vehicle-to-Everything (V2X) to revolutionize transportation.

Full‑time at the customer site in McLean, VA
.

• Be U.S. citizens or Green Card holders currently in the United States for the past three consecutive years and be eligible for a Public Trust Clearance.

We are seeking a motivated Transportation Engineer with experience in simulation and traffic operations to join our McLean, Virginia group. The successful candidate will engage in projects aiming to develop and optimize the use of advanced technologies (ITS, CDA, C‑V2X, CAV, AI‑driven predictive modeling) to improve the safety and operation of multimodal transportation systems.

• Develop, calibrate, and validate microscopic and mesoscopic traffic simulation models.
• Apply simulation tools to assess the safety, efficiency, and environmental impacts of advanced transportation strategies, including CAV and V2X applications.
• Support research into signal operations, signal control strategies, and traffic management applications.
• Collaborate with internal and external development teams to identify, understand, and resolve technical goals and challenges.
• Contribute to the development of Concept of Operations, system requirements, and technical guidance documents for transportation applications.
• Analyze simulation outputs and large‑scale datasets to explain transportation system performance.
• Document findings through technical reports, presentations, and manuals tailored to both technical and practitioner audiences.
• Generate synthetic data using Generative AI methods (e.g., GANs or LLMs for tabular data synthesis) using available historical data and known distributions.
• Provide technical assistance to academia, government, and industry stakeholders in the use of ITS, CDA, and V2X technologies.
• Support proposal development, white papers, and technical briefings.

• Master’s degree in Transportation Engineering or related fields.
• 2+ years of hands‑on experience with traffic simulation software such as VISSIM and/or Trans Modeler.
• Experience in signal operations and traffic control strategies (e.g., traffic signal timing, adaptive control, transit priority).
• Demonstrated ability to calibrate and validate simulation models.
• At least 1 year of experience collaborating with state and local DOTs.
• Strong analytical skills with the ability to interpret and present simulation and traffic data.
• At least 1 year of hands‑on experience in AI/ML model development, including building, training, and deploying models using Tensor Flow, PyTorch, or scikit‑learn.
• Proficiency in at least one programming language (Python, C++, Java, VBA, or Matlab).
• Experience writing and contributing to technical reports or research papers.
• Strong communication skills (writing, speaking, listening). Ability to articulate solutions and rationale for design decisions.
• Self‑motivated and focused on delivering outcomes.
• Ability to work independently and as part of large teams.
• Ability to obtain and maintain a Public Trust clearance (including three years of immediate residency in the US).
• All applicants must be legally authorized to work in the United States without company sponsorship.

• PhD degree in Transportation Engineering or related fields.
• In‑depth knowledge of CAV, Intelligent Transportation Systems, traffic operation and management.
• Knowledge or experience of AI model development, including reinforcement learning, computer vision, or LLMs applied to transportation systems.
• Experience integrating AI/ML models with transportation simulation tools for predictive analytics.
• Knowledge of co‑simulation tools.
• Experience…