2027 Summer Intern, MS/PhD, Software Engineer, Simulation Evaluation ML Model

What you'll do

• Create pipelines that turn simulation logs, trajectories, and behavioral events into structured graphs, and develop temporal graph models.
• Build and benchmark a hybrid retrieval engine for scenario discovery and automated failure analysis.
• Develop scenario exploration tools and collaborate with research and infrastructure teams on architecture and roadmap recommendations.

What they ask for

• Currently enrolled in a Master’s or PhD program in a relevant quantitative field, with at least one academic term remaining.
• Software development experience in Python and/or C++ in a Linux environment.
• Foundation in computer science, data structures, algorithm complexity, and distributed data systems.
• Hands-on experience with a modern deep learning framework such as PyTorch, JAX, or TensorFlow.

Nice to have

• Experience with knowledge graphs, graph algorithms, graph neural networks, or information retrieval/RAG.
• Experience with distributed data processing, temporal graphs, graph databases, or autonomous-vehicle simulation and related domains.

Pay

$70 — $70 USD (base hourly rate, Masters); $85 — $85 USD (base hourly rate, PhD)

Tools

Python, C++, Linux, PyTorch, JAX, TensorFlow, Apache Spark, Apache Beam

AI focus

Apply machine learning and graph modeling to represent, retrieve, and analyze multi-agent driving scenarios, supporting automated failure analysis.