This role involves designing, building, and maintaining scalable data processing systems for CrowdStrike's Intelligence team. You will work on large-scale distributed systems, interact with analysts, and ensure smooth operations of the systems you develop.
This role involves monitoring and analyzing security alerts using the CrowdStrike platform, conducting incident response across Windows, Mac, and Linux systems, and performing malware analysis and remediation. The analyst will contribute to a virtual security operations center, providing real-time threat detection and response for global customers while improving detection and countermeasure processes. The position emphasizes technical analysis, customer communication, and thought leadership in cybersecurity.
This role involves guiding EMEA-based AI companies in deploying and optimizing large-scale AI inference workloads on multi-node GPU clusters. The Senior Solutions Architect will design efficient inference pipelines for dense and sparse Mixture-of-Experts (MoE) models, improve performance through quantization and speculative decoding, and collaborate with NVIDIA’s product teams. The position also includes leading technical workshops and shaping next-generation inference architectures at the intersection of AI and high-performance computing.
This role involves architecting and optimizing large-scale AI inference solutions on multi-node GPU clusters, focusing on performance, efficiency, and reliability for leading AI organizations. You will guide customers in deploying dense and sparse Mixture-of-Experts models, optimize inference pipelines using advanced techniques like speculative decoding and quantization, and collaborate with NVIDIA product teams to drive innovation. The position also includes leading technical engagement through workshops and developing reference architectures for the EMEA region.
Develop and execute validation strategies for ADAS functions within Wayve’s AI Driver system, using simulation and real-world testing to ensure safety and performance. Define metrics, test coverage, and acceptance criteria in collaboration with cross-functional teams. Analyze results and drive validation processes from concept to implementation in a fast-paced, innovative environment.
Develop next-generation generative world models for autonomous driving, focusing on real-time simulation, closed-loop training, and scalable deployment. Work on high-performance diffusion and transformer-based models to enable efficient, interactive, and physically faithful driving simulations. Integrate models into production systems and mentor research teams in a fast-paced AI environment.
This role involves building and owning end-to-end machine learning components within a generative AI platform, with a focus on retrieval systems, knowledge representation, and RAG pipelines. The engineer will design and implement systems for knowledge retrieval, vector indexing, and context engines that power enterprise AI agents. Work includes developing evaluation frameworks, integrating with enterprise data sources, and collaborating across ML, product, and infrastructure teams to deliver high-impact AI solutions.
This role involves providing expert-level consultancy and strategic input to shape the development and evaluation of advanced generative AI systems. As a Research Advisor in the Human Frontier Collective, you'll collaborate on high-impact research, contribute to technical publications, and help design frameworks that translate domain expertise into AI model evaluation. The position offers flexible, part-time engagement with an interdisciplinary network of top-tier researchers and professionals.
Lead a team of data scientists who deliver experimental and observational analysis to accelerate the development of Wayve’s end-to-end AI for autonomous vehicles. Drive evals and insights from real and simulated driving data, enabling engineering teams to rapidly iterate and meet customer commitments. Scale impact through people, tooling, and automation in a fast-paced, innovative environment.
Design and execute automated tests for onboard software subsystems on embedded platforms, focusing on OS, middleware, sensors, and integration points. Work within hardware-in-the-loop environments to debug cross-layer issues and expand test coverage. Contribute to CI pipelines and reusable test frameworks to enable developer self-service testing and accelerate development cycles.
Investigate on-road incidents and recurring issues in Wayve's autonomous vehicle stack using data analysis, simulation, and cross-functional collaboration. Identify root causes across hardware, software, and AI models, then develop automated workflows and playbooks to improve resolution speed and system performance. The role involves deep technical investigation, clear communication of insights, and contributing to a safety-first culture.
Leads the end-to-end data strategy for autonomous driving AI, focusing on discovering and leveraging rare, safety-critical real-world driving data. Builds and scales global data systems across fleets, partners, and geographies to drive model performance improvements. Develops intelligent data selection, curation, and enrichment methods using embeddings, semantic search, and active learning.
Build and scale performance tooling for AI systems across cloud and embedded hardware, focusing on profiling, prediction, and optimization of deep learning models. Analyze bottlenecks across the full AI stack—from models to accelerators—and deliver data-driven insights to guide performance decisions. Collaborate with cross-functional teams to establish standards and drive efficiency in model training and inference.
Lead a growing engineering team building the real-time runtime platform for an AI-driven autonomous driving system. Focus on system design, middleware, performance optimization, and observability to enable reliable, low-latency operation across diverse vehicle platforms. Collaborate closely with software, hardware, and OEM teams to scale the AI Driver to new embodiments.
Optimise machine learning inference for edge accelerators and GPUs, focusing on efficient execution of large transformer models on low-power devices. Work across compilers, runtimes, kernels, and embedded deployment to deliver high-performance, reliable in-vehicle computing systems. Collaborate with model developers and contribute to technical roadmaps in an early-stage, high-impact environment.
