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About the Role

As a software engineer on Wayve’s Simulation Technology team, you will evolve a core component of Wayve’s simulation platform, which is critical for developing and evaluating Wayve’s driving intelligence. You will shape and implement the technical roadmap in areas such as robot emulator fidelity, visual fidelity, or efficient scaling, collaborating with various teams to ensure the platform meets user needs.

Responsibilities

Own key performance indicators (KPIs) for simulator cost, SLOs, throughput, and latency.
Collaborate cross-company on aligning technical dependencies for simulator implementation.
Lead technical discussions and guide technical direction.
Integrate components of the simulated robot into the simulation platform.
Integrate machine-learned graphics subsystems into the simulation platform.
Implement production-quality software in Python.

Requirements

Experience with workflow orchestration systems (e.g. Airflow, Dagster, Flyte) and/or developing data-intensive applications.
Deep knowledge of Kubernetes at the user level.
Good understanding of systems and data-oriented software engineering design principles.
Understanding of common software performance issues and design tradeoffs.
5+ years of industry experience designing and programming software.
Excellent communication and people engagement skills.

Skills

Python
Kubernetes
Workflow orchestration systems
Data-intensive applications
Systems and data-oriented software engineering design
Software performance analysis
Go
C++
Simulation scaling
Data-intensive workload scaling
Large-scale machine learning inference systems
Cloud GPU environments
Modern machine learned graphics techniques (NeRF, Gaussian Splatting, GenAI)

Location

London

Work Type

Full-time
Hybrid

Experience Level

5+ years of industry experience

About the Company

Wayve's approach to autonomous driving presents unique challenges for simulation, requiring a simulator that is both highly realistic and highly descriptive.
Our simulation approach combines classical techniques with machine learning to represent the real world in high fidelity at scale.