Applied Scientist / Machine Learning Engineer

A Masters with around 6 or more years of relevant experience, or a PhD with 2 or more years, in computer science, machine learning, robotics, mathematics, or a related field (required).

Strong ML and software fundamentals, and a track record of taking ML from research into production systems that run at scale.

Hands-on strength in one or more of: data curation, foundation model training, large-scale data wrangling, and foundation-model evaluation (for example, evaluation of LLMs or similar large models).

Experience with large-scale data and/or large neural networks, and the judgment to know which experiments and which data actually matter.

Fluency in Python and a modern deep-learning framework (PyTorch or similar), and comfort working with large, messy, real-world datasets.

Autonomous driving, robotics, or other embodied-AI domains.

Foundation models, VLMs, world models, diffusion or autoregressive generative models, or reinforcement learning and reward modeling.

Large-scale data infrastructure: embedding and vector search (e.g. turbopuffer, Milvus), distributed data processing (Ray Data, Daft, Spark), lakehouse formats (Lance, Iceberg), or annotation tooling.

Closed-loop or simulation-based evaluation, and safety-critical ML.

Publications at top ML, CV, or robotics venues (NeurIPS, ICML, ICLR, CVPR, CoRL, RSS).

This is a full-time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $311,850 to $370,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.