Lead business development and delivery for AI-driven simulation software within aerospace and defense, driving customer acquisition, shaping go-to-market strategy, and managing technical execution. Engage with senior engineering leaders, scope and deliver high-impact projects, and translate customer needs into product evolution. This hybrid role blends strategic sales with hands-on technical leadership and regular travel to customer sites.
This role involves building and running high-fidelity CFD simulations from geometry preparation to post-processing for moderately complex engineering cases. You'll work at the intersection of CAE and data science, supporting the development of AI-driven simulation models and contributing to automated workflows on cloud and HPC platforms. The position includes customer collaboration, model adaptation for deep learning surrogates, and occasional international travel to support on-site engagements.
Act as a technical bridge between Wayve and automotive OEMs/Tier 1 suppliers, defining integration architecture for autonomous driving systems. Translate customer requirements into technical specifications, clarify interface boundaries, and ensure safe, scalable integration of AI-driven software into vehicle platforms. Work across software, safety, and validation teams in a fast-paced environment focused on mapless, AI-powered automation.
Integrates and brings up autonomous driving systems across internal and partner vehicles, working at the intersection of hardware and software. Leads multidisciplinary troubleshooting, system architecture, and development infrastructure for embodied AI in robotics and automotive contexts. Builds tooling and processes to accelerate reliable deployment from prototype to production.
Design and optimize high-performance AI inference systems for large-scale models using cutting-edge GPU hardware. Develop and enhance inference frameworks like vLLM, implement advanced parallelism techniques, and contribute to compiler and kernel optimization. Build scalable scheduling solutions for multi-node, multi-cloud GPU deployments and drive industry benchmarks such as MLPerf.
This role involves researching and developing GPU-accelerated techniques for deep learning, machine learning, and other AI workloads. You'll collaborate with technical experts in industry and academia to deeply analyze and optimize complex AI and high-performance computing (HPC) algorithms for modern CPU and GPU architectures. The position also includes influencing future hardware and software design at NVIDIA and sharing optimization insights through blogs and conferences.
This role involves end-to-end ownership of specific ADAS features such as TFL, Blind Spot Monitoring, and Cross Traffic Alert, ensuring they meet OEM requirements and are delivered to specification. The Feature Owner collaborates closely with engineering, product, and external partners to define scope, set performance targets, and support validation. The position requires deep technical understanding of ADAS systems, strong cross-functional coordination, and alignment of customer needs with Wayve’s strategic roadmap.
This role involves building and scaling the reliability foundations of an AI cloud platform, including model development and GPU compute systems. The engineer will define SRE frameworks, ensure platform resilience, and enable scalable AI deployment through automation and observability. It's a founding role requiring deep expertise in distributed systems, Kubernetes, and cloud infrastructure.
The role involves managing and executing commercial partnerships for Wayve’s robotaxi deployments in London or Tokyo, working closely with ride-hailing platforms, OEMs, and internal teams to ensure successful pilot launches and fleet scaling. The individual will coordinate technical integration, track performance KPIs, and manage risks across complex, regulated environments. This is a high-impact position at the intersection of AI-driven autonomy and mobility ecosystems, requiring both strategic vision and hands-on operational execution.
This role involves defining and driving the product roadmap for Level 4 autonomous driving features, translating advanced embodied AI and end-to-end learning technologies into safe, user-centric AV solutions. The Technical Product Manager will work cross-functionally with R&D, safety, validation, and commercial teams to deliver market-ready features, with a strong focus on regulatory alignment, customer needs, and real-world deployment. The position emphasizes ownership of the full product lifecycle, from concept through to production, within a fast-paced, innovation-driven environment.
Design and optimize compiler technologies for NVIDIA's CPUs, focusing on hardware-software co-design to enhance performance for AI and high-performance computing workloads. Collaborate with distributed teams and open-source communities to develop advanced compiler features and contribute to next-generation compute platforms. Analyze real-world workloads to drive improvements in both compiler toolchains and future CPU architectures.
This role involves researching and developing GPU-accelerated techniques for AI and high-performance computing workloads. You'll collaborate with experts in industry and academia to optimize complex algorithms on modern CPU and GPU architectures, while contributing to the design of future hardware and software platforms. The position emphasizes deep technical optimization, publication of findings, and engagement with the developer community.
Research and develop GPU-accelerated techniques for deep learning, machine learning, and AI workloads. Collaborate with technical experts in industry and academia to optimize complex AI and HPC algorithms on modern CPU and GPU architectures. Publish findings in developer blogs or conferences and influence next-generation hardware and software design at NVIDIA.
This role involves developing high-performance CPU compilers for NVIDIA's next-generation computing platforms, with a focus on AI and HPC workloads. You'll work on hardware-software co-design, optimising compiler toolchains for NVIDIA CPUs like Grace, and contributing to open-source projects such as LLVM and GCC. Collaboration with pre-silicon teams and upstream communities is central to improving performance across data centres and supercomputing environments.
This role involves developing and optimizing compiler software for NVIDIA's CPUs, with a focus on performance in AI and high-performance computing workloads. You'll work on hardware-software co-design, contribute to open-source compiler projects like LLVM or GCC, and collaborate with distributed teams to improve compiler toolchains. The position is central to advancing NVIDIA's next-generation computing platforms in data centers and supercomputing environments.
