Software Engineer, AI Platform & ML Tools

EngineersOfAI; Greater London; Hybrid; GBP 75,000 - 110,000; Full time

Job summary

Wayve is seeking a Software Engineer for its AI Libraries team to build and maintain scalable Python libraries and tools for ML engineers and researchers. You will design abstractions for data loading, distributed training, and model evaluation, while ensuring reliability and documentation.

Collaborate with ML teams to optimize training on large GPU clusters and cloud infrastructure, advancing Wayve’s autonomous driving platform with robust, scalable software.

Qualifications

• Proven ability to design and deliver software systems.
• Experience building tools or libraries for internal or external users.
• Strong testing, observability, maintainability practices.

Responsibilities

• Design, build, and maintain scalable Python libraries and tools used by ML engineers and researchers across Wayve.
• Develop robust abstractions for data loading, distributed training, inference, checkpointing, and model evaluation workflows.
• Support training at scale across large GPU clusters and cloud-based infrastructure.
• Work closely with ML teams to understand user needs and create tools that are reliable, well-documented, observable, and easy to adopt.
• Improve engineering quality across ML systems through strong software architecture, testing, monitoring, and maintainability practices.
• Optimize data and training pipelines to support multi-modal data sources, including camera, radar, lidar, and other sensor data.
• Contribute to the evolution of Wayve’s AI platform as we scale our autonomous driving capabilities.

Skills

Python

Software architecture

Distributed computing

ML frameworks (PyTorch, TensorFlow)

Cloud platforms (Azure)

Testing & observability

Team collaboration

Tools

Azure

Job description

Wayve is seeking a Software Engineer for its AI Libraries team to build and maintain scalable Python libraries and tools for ML engineers and researchers. You will design abstractions for data loading, distributed training, and model evaluation, while ensuring reliability and documentation.

Collaborate with ML teams to optimize training on large GPU clusters and cloud infrastructure, advancing Wayve’s autonomous driving platform with robust, scalable software.