Applied Scientist: Data Curation for Driving AI

OpenDigital Limited; Sunnyvale, Northern (CA, KY); Hybrid; USD 312,000 - 370,000; Full time

Benefits offered by this job

Hybrid work model

Equity package

Job summary

Wayve in Sunnyvale seeks a senior Applied Scientist or Machine Learning Engineer to advance data curation, enrichment, and foundation-model evaluation for embodied AI driving systems. You will work across data tooling, model training, and offline/closed-loop evaluation to accelerate model generalisation across geographies and vehicles.

The role offers a hybrid work model in a fast-paced environment; the team values rigorous data pipelines, research-to-production experience, and collaboration

Qualifications

• Masters with 6+ years in CS/ML or PhD with 2+ years (required).
• Strong ML fundamentals; production-ready ML from research to large-scale systems.
• Hands-on in data curation, foundation-model training, large-scale data wrangling, and evaluation.
• Experience with large-scale data and large neural networks.
• Fluency in Python and modern DL frameworks (PyTorch or similar).
• Desirable: autonomous driving, foundation models, VLMs, and large-scale data infra.

Responsibilities

• Mine world-scale fleet data for rare, safety-critical moments.
• Turn raw driving data into high-signal training data via (semi-)automated enrichment and labeling.
• Build high-quality data enrichments and data-quality pipelines at scale.
• Build and fine-tune large-scale pretrained models and run experiments to derisk ideas.
• Contribute to embodied VLM/VLA stacks (LINGO) and evaluation frameworks.
• Design offline and closed-loop evaluation with robust metrics for real-world safety.

Skills

Python

PyTorch

Data wrangling

Production ML

Communication

Education

Master's degree in CS/ML

PhD in a related field

Tools

Milvus

Ray

Spark

Job description

Wayve in Sunnyvale seeks a senior Applied Scientist or Machine Learning Engineer to advance data curation, enrichment, and foundation-model evaluation for embodied AI driving systems. You will work across data tooling, model training, and offline/closed-loop evaluation to accelerate model generalisation across geographies and vehicles.

The role offers a hybrid work model in a fast-paced environment; the team values rigorous data pipelines, research-to-production experience, and collaboration