1 day ago
London, United KingdomMid Level
Responsibilities
- Design, build, and maintain scalable Python libraries and tools for ML engineers and researchers.
- Develop abstractions for data loading, distributed training, inference, checkpointing, and model evaluation.
- Support training at scale across GPU clusters and cloud infrastructure.
- Partner with ML teams to understand needs and create reliable, documented, observable, and adoptable tools.
- Improve architecture, testing, monitoring, maintainability, and engineering quality across ML systems.
- Optimize data and training pipelines for camera, radar, lidar, and other multimodal sensor data.
- Contribute to the evolution of Wayve’s AI platform for autonomous driving.
Requirements
- Strong Python programming experience and proven experience delivering software systems from concept through completion.
- Strong software architecture and system design skills, including experience building tools, platforms, or libraries.
- Strong understanding of testing, observability, maintainability, and engineering best practices.
- Experience working with cloud environments, ideally Azure.
- Experience with concurrent, parallel, or distributed computing.
- Familiarity with ML frameworks such as PyTorch, TensorFlow, or PyTorch Lightning.
- Ability to work with technical stakeholders to refine requirements and deliver scalable solutions.
- Experience with large GPU clusters, distributed training environments, DDP, or FSDP is desirable.
- Experience with Prometheus, Grafana, Datadog, OpenTelemetry, Airflow, Flyte, Ray, Metaflow, Argo Workflows, Docker, Kubernetes, Terraform, or NVIDIA Nsight is desirable.
- Understanding of ML workflows or experience working with researchers is desirable.
Benefits
- Work on high-impact systems supporting autonomous-driving technology.
- Help scale training and evaluation infrastructure across large GPU clusters.
- Build software used by ML engineers and researchers working on embodied AI.
- Join a team focused on strong engineering standards, practical abstractions, and scalable platform design.
- Contribute to bringing autonomous-driving technology closer to real-world deployment.
- Wayve supports an inclusive interview experience and provides accommodations or adjustments when needed.
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