Autonomous Driving AI Evaluation Fellow

Johns Hopkins University

Gaithersburg (MD)

On-site

USD 77,000 - 94,000

Full time

14 days+

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Job summary

Johns Hopkins University is seeking a PREP Research Associate to support the independent evaluation of AI-enabled decision-making for automated vehicles. The role focuses on simulation engineering (CARLA, SUMO) and software integration (toolkits, APIs) within an open-source evaluation framework, with emphasis on reproducible, auditable evaluation.

The position requires an MS/PhD in CS/Robotics/AI or related fields, strong Python/C++ skills, and experience with AV stacks, OpenSCENARIO, and

Qualifications

MS or PhD in Computer Science, Robotics, AI, or related engineering fields.
Strong programming experience in Python and C++.
Experience with autonomous vehicle simulation environments (CARLA, SUMO).
Experience with OpenSCENARIO scenario description language.
Experience building software toolkits, APIs, and standardized interfaces; familiarity with Docker.
Knowledge of autonomous vehicle systems architecture and behavioral planning concepts.
Experience with ROS 2 on Linux.
Experience with version control (Git/GitHub/GitLab).
Familiarity with data modeling, schema design, and validation methodologies.

Responsibilities

Simulation engineering: manage CARLA simulation infra and scenario execution pipeline.
Configure multi-agent traffic behavior with IDM/MOBIL and learned agents.
Integrate hardware-in-the-loop testing and optimize large-scale runs.
Support integration of open-source stacks (e.g., Autoware) to test architectures.
Software integration: develop evaluation toolkit and API; define interfaces.
Implement standardized logging schema for interoperable evaluation.
Build containerized deployment pipeline (Docker) and hashing schema.
Produce automated reporting templates and documentation.