2 months ago
Base Salary
$312k - $370k/yr
Responsibilities
- Build, train, fine-tune, and adapt computer vision and scene-understanding models for offline measurement.
- Improve model accuracy and generalization across vehicle platforms, geographies, and driving conditions.
- Use larger models, higher compute budgets, bidirectional temporal context, and multi-task or joint representation learning.
- Define benchmarks, quality bars, metrics, error analysis, and correctness criteria for model evaluation.
- Ensure results are statistically defensible and suitable for validation pipelines and safety cases.
- Collaborate with on-vehicle modeling, evaluation, data curation, and simulation teams, while mentoring other engineers.
Requirements
- 4+ years of ML engineering experience, including training and shipping deep-learning models in production.
- Hands-on experience training modern computer vision models, including transformer-based and multimodal or VLM architectures, for detection, segmentation, classification, or scene understanding.
- Experience adapting or fine-tuning large pretrained or foundation models and training shared representations across multiple tasks or objectives.
- Proficiency in Python and ML frameworks, especially PyTorch, with strong software-engineering practices and comfort with large-scale training.
- Ability to independently lead significant modeling workstreams, collaborate across teams, and mentor less experienced engineers.
- Ability to define and interpret metrics that demonstrate genuine model improvement.
- Preferred experience with 3D scene understanding, geometric and semantic perception, driving-scene enrichment, offline modeling, auto-labeling, model distillation, temporal or world models, autonomous vehicles or robotics, physical-system validation, fleet-scale data, or distributed training infrastructure.
Benefits
- Full-time position based in the Sunnyvale office.
- Hybrid working policy combining office and workshop collaboration with working from home.
- Competitive equity package.
- Inclusive interview experience with accommodations available upon request.
Categories
About Wayve
Wayve builds end-to-end autonomous driving software—the vehicle-agnostic Wayve AI Driver—that runs on onboard compute and native sensors, licensed to automakers and fleet operators. Its platform spans ADAS and higher autonomy (L2+/L3 to robotaxi) and is designed to generalize across vehicle types and geographies. Founded in 2017 and headquartered in London, it tests its models across Europe, North America, and Japan, with a U.S. base in Sunnyvale, CA.