Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate directly with customers and technical teams to prototype, deploy, and iterate on high-impact tools across aerospace, energy, and advanced manufacturing. Work across backend services, APIs, and cloud infrastructure while contributing to core platform development.
Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate with data scientists and customers to develop, prototype, and deploy production-grade tools using Python, FastAPI, and cloud infrastructure. Work across industries such as aerospace, energy, and semiconductors, with opportunities for international travel to support on-site customer deployments and iterate on solutions based on direct user feedback.
This role involves driving adoption of NVIDIA's AI and accelerated computing platforms within the manufacturing sector across EMEA. You'll work directly with developers, ISVs, startups, and industrial enterprises to build solutions in robotics, digital twins, computer vision, and predictive maintenance. The position focuses on technical enablement through workshops, reference architectures, and co-innovation, while bridging developer feedback to internal product and engineering teams.
Design and lead the evolution of large-scale AI infrastructure for training and inference workloads across thousands of GPUs and petabyte-scale data systems. Enable seamless cross-region execution and data federation to support Wayve's embodied AI and autonomous driving research. Provide strategic technical leadership and mentorship across engineering teams.
Develop and refine vehicle trajectory and motion controllers that translate AI-driven decisions into safe, smooth vehicle movement across diverse platforms. Work on real-time control systems using C++, integrating with AI components and validating performance through simulation and on-road testing. Collaborate across teams to support new vehicle platforms and autonomous driving features.
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.
Develop a physics-informed neural network-based computational fluid dynamics simulator for offshore renewable energy applications, integrating deep learning with fluid dynamics models and embedding the solution into OpenFOAM. The role combines PhD research with teaching, focusing on improving simulation efficiency and robustness for complex engineering problems.
The COE Specialist ensures the smooth operation of business systems by monitoring, resolving, and escalating incidents within a 24x7 support environment. This role involves hands-on troubleshooting of hardware, software, and network issues, coordinating with engineering and technology teams to restore services quickly. The specialist acts as a technical point of contact, managing ticketing, incident prioritization, and communication to minimize customer impact during outages.
Monitor and provide technical support for operations within automated warehouses, ensuring smooth functioning of robotic systems and resolving incidents. Act as a liaison between client teams and engineering, managing incident resolution and system performance. Work on rotating shifts with a focus on operational efficiency and timely issue escalation.
A 4-month, full-time fellowship program offering mentorship and funding for technical talent to conduct empirical AI research aligned with Anthropic’s priorities in AI safety, security, systems, reinforcement learning, or policy. Fellows work on a project with the goal of producing a public output such as a research paper, supported by Anthropic researchers and access to compute resources.
This role involves a 4-month, full-time research fellowship focused on ML systems and performance, with mentorship from Anthropic researchers. Fellows will work on empirical projects using external infrastructure to build scalable ML systems, debug training processes, and support high-performance computing environments. The program emphasizes collaboration, rapid implementation, and producing public research outputs such as papers.
Lead the technical design and development of virtual reality simulation systems using Unreal Engine for defence applications. You will oversee code architecture, mentor a development team, and evaluate emerging technologies such as AI and AR. The role involves close collaboration with external partners and internal teams in a hybrid setup near Portsmouth.
Design and optimize machine learning models for hardware acceleration on platforms such as GPUs and QPUs, focusing on low-latency distributed systems and simulation. Work independently within an established team to support international clients using cutting-edge technologies. The role involves algorithm development in C++, Python, or Rust, with a strong emphasis on performance and hardware integration.
This role involves analysing manufacturing, quality, and product performance data to uncover trends and drive engineering improvements. You'll develop analytical models and dashboards, apply machine learning techniques, and collaborate with engineering and digital teams to support data-driven decision-making. The position emphasizes translating complex data into actionable insights for both technical and non-technical audiences.
Develop advanced mathematical and machine learning models for complex industrial and scientific systems by combining first-principles physics with AI techniques. Work across the full modelling lifecycle using large-scale sensor and operational data to build predictive digital representations of physical processes. Collaborate with a high-calibre team to improve model performance through experimental design and real-world validation.
