2027 Summer Intern, MS/PhD, Software Engineer, Simulation Evaluation ML Model
Waymo · Mountain View, California, USA
About this role
**Waymo — 2027 Summer Intern (MS/PhD), Software Engineer — Simulation Evaluation ML Model** Waymo is an autonomous driving technology company on a mission to be the world’s most trusted driver. Waymo’s Driver powers its fully autonomous ride-hail service and is built on extensive real-world driving experience and large-scale simulation. ## What you will do - Design and implement an automated semantic extraction pipeline to parse large-scale simulation logs, vehicle trajectory data, and multi-agent behavioral events into structured graph representations (entities, temporal relationships, and causal interactions). - Develop temporal graph modeling techniques for time-varying multi-agent interactions, road context, and safety-critical driving events. - Build a multi-modal hybrid retrieval engine (dense vector embeddings + keyword search + graph traversal) to enable fast scenario discovery and serve as structured memory for automated failure analysis agents. - Create interactive data exploration tools and visualization dashboards (e.g., Jupyter/Colab-based explorers) to help autonomy engineers and researchers analyze complex scenario distributions. - Benchmark retrieval precision, recall, and query latency against traditional tabular and relational search baselines. - Collaborate cross-functionally with simulation researchers, ML engineers, and software infrastructure teams to document system architecture and recommend a roadmap. ## What you have - 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. - Strong software development experience in Python and/or C++ in a Linux development environment. - Solid foundation in core computer science concepts, data structures, algorithm complexity, and distributed data systems. - Hands-on experience with modern deep learning frameworks (e.g., PyTorch, JAX, or TensorFlow). ## We prefer - Research 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 venues (e.g., NeurIPS, ICML, ICLR, KDD, 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. - Interest or domain experience in autonomous vehicle simulation, behavior prediction, motion planning, trajectory forecasting, or multi-agent interaction modeling. ## General perks - Work on challenging problems with direct impact. - Competitive compensation packages (including housing/relocation bonus if applicable). - Medical, dental, and vision insurance. - Fun intern events and networking opportunities. ## Onsite perks - Free breakfast, lunch, dinner, and snacks. - Free access to Google shuttles. - Onsite gym. ## Notes - This is a **hybrid onsite** internship. - Resumes are accepted on a **rolling basis** until the role is filled. - If applying to multiple roles, apply to each one individually—please apply to the **top 3 roles** you’re interested in. ## Pay transparency (hourly) - **Hourly Masters Pay:** $70 USD/hr - **Hourly PhD Pay:** $85 USD/hr
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