Wayve
United Kingdom
Data Scientist
- AI
- Distributed Computing
- Hadoop
- Machine Learning
AI Summary
Key Highlights
Revamp Harness system and develop DAG-based orchestration for high-volume autonomous driving data.
Build scalable infrastructure for data ingestion, processing, inference, and evaluation workflows.
Support batch inference, performance optimization, and incident response aligned with SLOs.
Key Responsibilities
Design and evolve scalable data pipeline and orchestration infrastructure for autonomous driving platforms.
Revamp existing Harness system and develop a DAG-based workflow platform for high-volume fleet data.
Build tooling and libraries for reliable, efficient data ingestion, processing, inference, and evaluation workflows.
Ensure efficient execution of hundreds of parallel pipeline steps with correct outputs and resource prioritization.
Support batch inference, performance optimization, and incident response workflows aligned with SLOs.
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Technical Skills Required
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Benefits & Perks
Meaningful equity and long-term ownership
Hybrid working with core hours
Learning and development budgets (training, conferences, growth)
Comprehensive benefits including health insurance, dental, enhanced maternity/paternity leave, retirement, wellbeing partnerships, and team socials
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Nice to Have
Experience with machine learning infrastructure or inference systems.
Exposure to large-scale batch processing or compute scheduling.
Experience building shared libraries or internal platforms used across multiple teams.
Job Description
Before the detail, here's the challenge you'd help us solve.
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.
Here’s what this particular role covers.
About our Engineering Teams
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