Software Engineer 2027 Summer Intern (Simulation Evaluation ML Model, MS/PhD)
Waymo · Mountain View, CA, United States
About The Role
Join Waymo, a leader in autonomous driving technology, as a Software Engineer Intern for the summer of 2027. In this role, you will design and implement an automated semantic extraction pipeline, develop temporal graph modeling techniques, build a multi-modal hybrid retrieval engine, create interactive data exploration tools, and benchmark retrieval precision. You will collaborate with simulation researchers, machine learning engineers, and software infrastructure teams, and have a direct impact on the company. This is a hybrid onsite internship position with numerous benefits, including medical, dental, and vision insurance, competitive compensation, and paid time off.
- Design and implement an automated semantic extraction pipeline that parses large-scale simulation logs, vehicle trajectory data, and multi-agent behavioral events into structured graph representations.
- Develop temporal graph modeling techniques to capture time-varying multi-agent interactions, road context, and safety-critical driving events.
- Build a multi-modal hybrid retrieval engine to enable fast scenario discovery and serve as structured memory for automated failure analysis agents.
- If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you
- Hands-on experience with modern deep learning frameworks (such as PyTorch, JAX, or TensorFlow)
- Strong software development experience in Python and/or C++ in a Linux development environment
- Currently enrolled in a graduate program (PhD or Master’s) in Computer Science, Artificial Intelligence, Robotics, Electrical Engineering, or a related quantitative field, with at least one academic term remaining
- Solid foundation in core computer science concepts, data structures, algorithm complexity, and distributed data systems
- Demonstrated research background or practical experience in Knowledge Graphs, Graph Algorithms, Graph Neural Networks (GNNs), or Information Retrieval / Retrieval-Augmented Generation (RAG)
- Authorship of published papers in top-tier AI/ML, data mining, or computer vision conferences (e.g., NeurIPS, ICML, ICLR, KDD, The Web Conference [WWW], CVPR, CoRL, SIGMOD, VLDB, ACL)
- Experience with large-scale distributed data processing systems (e.g., Apache Spark, Apache Beam, distributed SQL query engines, or columnar data lakes)
- Familiarity with temporal graphs, bi-temporal data modeling, or graph databases/tooling
- Demonstrated interest or domain experience in autonomous vehicle simulation, behavior prediction, motion planning, trajectory forecasting, or multi-agent interaction modeling
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