1 day ago
London, United KingdomStaff+
Responsibilities
- Collaborate with ML engineers, data engineers, and product teams to deliver features end to end.
- Review model and metric changes and evaluation results against quality and safety standards before release.
- Identify ML delivery pipeline bottlenecks and drive improvements that increase speed without compromising quality.
- Define and build checks and automation with AI Platform teams to detect issues earlier.
- Work with CI/CD teams to adapt workflows and streamline model delivery.
- Partner with evaluation teams to improve evaluation reliability, identify gaps, and develop new evaluation methodologies.
- Stay current with MLOps practices and tools and incorporate improvements into workflows.
Requirements
- Experience introducing operational processes that improve engineering excellence and the ability to think across full systems.
- Strong MLOps, model registry, and ML lifecycle experience.
- Deep technical understanding of ML training.
- Strong understanding of ML code infrastructure and best practices, including PyTorch, TensorRT, quantization, and model deployment.
- Strong GitHub Actions experience.
- Strong communication skills and a collaborative mindset.
- Experience with Grafana monitoring and production observability is desirable.
Benefits
- Full-time role based in Wayve’s London office.
- Hybrid working policy combining time in the office and workshops with time working from home.
- Inclusive interview experience with accommodations or adjustments available upon request.
Tech Stack
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