обновлено 6 дней назад
Senior Software Engineer, Cloud, Simulation (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Software Engineer, Cloud, Simulation (AI): Evolving a high-fidelity simulation platform for autonomous driving with an accent on scalable cloud infrastructure, workflow orchestration, and machine-learned graphics. Focus on integrating simulated robotics and graphics components, optimizing simulator cost and throughput, and building production-quality Python software for large-scale simulation workloads.
Location: London, United Kingdom; hybrid role based in the London office
Company
develops embodied AI software and foundation models for intelligent, mapless, and hardware-agnostic automated driving systems.
What you will do
- Evolve a core component of the simulation platform used to develop and evaluate driving intelligence.
- Shape and implement the technical roadmap for robot emulator fidelity, visual fidelity, or efficient scaling.
- Own simulator KPIs covering cost, service-level objectives, throughput, and latency.
- Integrate simulated robot components and machine-learned graphics subsystems into the platform.
- Align technical dependencies across robotics, research, platform, data, and simulation teams.
- Lead technical discussions and implement production-quality software in Python.
Requirements
- 5+ years of industry experience designing and programming software.
- Experience with workflow orchestration systems such as Airflow, Dagster, or Flyte, and/or data-intensive applications.
- Excellent Python development skills.
- Deep user-level knowledge of Kubernetes.
- Strong systems and data-oriented software engineering design skills, including reusable and extensible code.
- Understanding of software performance issues, design trade-offs, communication, and cross-functional collaboration.
Nice to have
- Experience in autonomous vehicles or robotics.
- Proficiency in Go or C++.
- Experience scaling simulations or data-intensive workloads.
- Experience optimizing large-scale machine learning inference systems in cloud GPU environments.
- Experience operating and scaling machine-learned graphics techniques such as NeRF, Gaussian Splatting, or GenAI.
Culture & Benefits
- Hybrid work combining time in offices and workshops with working from home.
- Core working hours with flexibility to determine a suitable schedule.
- Inclusive and respectful work environment that values diverse perspectives.
- Collaboration across robotics, research, platform, data, and simulation teams.
Hiring process
- Interview accommodations and adjustments are available upon request.
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