AI for Autonomous Vehicles Research Fellow

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 110,000; Full time

Job summary

Johns Hopkins University, through the PREP program with NIST, conducts independent evaluation of AI decision-making for automated vehicles. The role focuses on simulation engineering using CARLA and multi-agent traffic modeling, and software integration for an open-source evaluation toolkit.

Collaboration spans AV research and open-source tool development. The candidate will work on scalable testing pipelines, containerized deployments, and standardized data logging to support reproducible

Qualifications

• MS required (PhD preferred) in Computer Science, Robotics, AI/Machine Learning, or related engineering fields.
• Strong programming experience in Python and C++.
• Experience with autonomous vehicle simulation environments (CARLA, SUMO, or similar) and OpenSCENARIO.
• 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 systems.
• Experience with version control software and workflow (Git/GitHub/GitLab).
• Familiarity with data modeling, schema design, and validation methodologies.

Responsibilities

• Simulation Engineering: Manage CARLA simulation infrastructure and run OpenSCENARIO 2.0 test cases.
• Configure multi-agent traffic behavior with layered models for large-scale evaluation runs.
• Integrate hardware-in-the-loop testing and optimize performance for large-scale multi-agent test runs.
• Support integration of open-source automated driving stacks (e.g., Autoware) to test architectures.
• Software Integration: Develop the open-source evaluation toolkit and design the Evaluation Gateway API and standardized interfaces.
• Implement the standardized behavioral data logging schema for interoperable evaluation.
• Build containerized deployment pipelines (Docker) and the Cryptographic Hashing Message Schema.
• Produce automated reporting templates and technical documentation for reproducible evaluation.

Skills

Python

C++

ROS 2

Git/GitHub/GitLab

Autonomous vehicles

CARLA / SUMO

OpenSCENARIO

Data modeling

Schema design

Education

MS in CS/Robotics/AI

Tools

Docker

Job description

Johns Hopkins University, through the PREP program with NIST, conducts independent evaluation of AI decision-making for automated vehicles. The role focuses on simulation engineering using CARLA and multi-agent traffic modeling, and software integration for an open-source evaluation toolkit.

Collaboration spans AV research and open-source tool development. The candidate will work on scalable testing pipelines, containerized deployments, and standardized data logging to support reproducible