Senior ML Engineer - Autonomous Driving Platform

Wayve; Sunnyvale (CA); Híbrido; USD 140.000 - 200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Equity participation

Relocation support

Hybrid working model

Learning & development budgets

Comprehensive benefits

Descripción de la vacante

Wayve is seeking an experienced ML Engineer to advance our AI driver model architecture and training pipelines in Sunnyvale. You will own the data strategy, evaluation metrics, and iteration cycles, enabling robust end-to-end delivery from data to deployed models.

You will work with multi-sensor inputs, develop production-grade ML systems, and collaborate across teams to scale the autonomous driving platform in real-world scenarios.

Formación

• Proven track record training deep learning models with end-to-end ownership.
• Experience taking ML models into production, handling real-world constraints, quality and safety requirements.
• Strong Python skills and hands-on experience with modern ML frameworks.
• Background in either end-to-end autonomous driving/embodied AI or large-scale product ML systems.
• Familiar with model compression and deploying ML to embedded systems (nice to have).

Responsabilidades

• Develop the AI driver model architecture and training algorithms for L2/L3/L4 driving behaviours.
• Own training lifecycle, including evaluation strategy, success metrics, and iteration planning.
• Curate real-world and synthetic data to teach driving behaviours and support training.
• Run on-road and offline experiments; translate results into concrete next steps and improvements.
• Build production-ready ML systems with strong software engineering, quality, and reliability practices.

Conocimientos

Deep learning

Python

Production ML

Reinforcement learning

Behavioural cloning

Model training

Data pipelines

Herramientas

PyTorch

TensorFlow

scikit-learn

Descripción del empleo

Wayve is seeking an experienced ML Engineer to advance our AI driver model architecture and training pipelines in Sunnyvale. You will own the data strategy, evaluation metrics, and iteration cycles, enabling robust end-to-end delivery from data to deployed models.

You will work with multi-sensor inputs, develop production-grade ML systems, and collaborate across teams to scale the autonomous driving platform in real-world scenarios.