Develop automated tools for large-scale data analysis, vulnerability research, and exploit development. Investigate 0-day and n-day vulnerabilities by analyzing patches, malware, and system logs. Collaborate across teams to support threat intelligence and publish findings in blogs or conferences.
Conducts advanced vulnerability research and exploit development, analyzing patches and malicious artifacts to identify 0-day and n-day vulnerabilities. Develops automated tools for large-scale data analysis and collaborates across teams to publish findings and support threat intelligence efforts. Focuses on reverse engineering, proof-of-concept creation, and rapid response to emerging threats.
This role involves partnering with academic and research institutions to advance the use of NVIDIA's accelerated computing and AI technologies. The Solutions Architect will guide researchers in integrating NVIDIA's software stack and hardware platforms into high-impact scientific projects, deliver technical training, and translate research needs into product feedback. The position requires deep expertise in multimodal AI, robotics, and large-scale GPU systems, with a strong emphasis on collaboration, prototyping, and thought leadership in the research community.
This role involves conducting cutting-edge research in reinforcement learning and large language models to advance intelligent systems. You'll co-develop models that enhance memory, task horizon, and general intelligence in vision-language models, with a strong emphasis on open-sourcing code and publishing high-impact research. The position is embedded in NVIDIA's AI research team in Zurich, focusing on long-term breakthroughs in AI.
This role involves developing and deploying AI-driven models for high-fidelity, multi-physics simulation in engineering and manufacturing. The Principal Data Scientist will lead technical initiatives, design deep learning architectures, and integrate predictive models with simulation systems. They will work closely with cross-functional teams and customers to solve complex engineering challenges, mentor junior staff, and drive R&D innovation across global sites.
This role involves deploying and scaling machine learning models for high-fidelity engineering simulations, working directly with customers to integrate AI into production environments. The Principal ML Engineer will lead technical architecture, build robust data and inference pipelines using Python, PyTorch, and Kubeflow, and mentor teams across global customer sites. The position bridges advanced physics-based challenges with practical AI solutions in industries like aerospace, energy, and semiconductors.
As an Applied AI Engineer at Anthropic, you will serve as a technical advisor to tech-forward companies, helping them build on the Claude Developer Platform. You'll work hands-on with customer engineering teams, develop custom evaluation frameworks, and create technical resources to enable successful AI applications.
This role involves designing and running measurement frameworks for offline marketing campaigns, including geo holdout tests, media mix modelling, and incrementality studies. You will partner closely with Marketing leadership and the Growth Data team to ensure consistent and effective marketing strategies.
The role involves deep expertise in a specific reliability domain such as observability, performance engineering, or security-focused SRE, with responsibility for defining standards, building automation, and improving system resilience across a cloud-native platform. The engineer will lead incident response, develop tooling for scalability, and integrate reliability practices across Platform Engineering and DevSecOps. Emphasis is placed on cross-team collaboration, operational excellence, and driving long-term fixes for complex systemic issues.
Design and build scalable backend systems for detecting and preventing abuse of free-tier services, focusing on AI-driven moderation and guardrails. Develop production-grade APIs, data pipelines, and observability frameworks while collaborating with ML engineers to deploy models at scale. Own end-to-end technical execution of safety infrastructure across a multimodal AI platform.
This role focuses on designing and operating large-scale AI infrastructure, specifically managing the lifecycle of compute nodes across cloud and on-prem environments. The engineer will lead technical strategy for node provisioning, health monitoring, and automated repair systems, ensuring high reliability and efficiency across Anthropic's GPU, TPU, and Trainium fleets. Collaboration with research, inference, and cloud provider teams is central to shaping long-term infrastructure and compute strategy.
This role involves shaping the Network Detection and Response (NDR) product within Darktrace’s AI-driven cybersecurity platform. The Product Manager will bridge customer needs, technical development, and go-to-market strategy, working closely with R&D, marketing, and sales teams. Key responsibilities include defining product direction, validating features, and ensuring effective internal and external communication of product capabilities.
This role involves designing, developing, and deploying scalable data pipelines using Azure Databricks, Azure Data Factory, and Azure SQL Database. You will work on high-impact insurance data transformation programs, ensuring data quality, performance, and security, and collaborate with experienced data professionals in a forward-thinking environment.
This role involves working closely with Databricks' largest enterprise customers across the UK and Ireland to drive digital transformation through data and AI. As a technical leader, you'll shape long-term data strategies, build executive-level relationships, and lead complex integrations across cloud ecosystems like AWS, Azure, and GCP. You'll also mentor internal teams, develop best practices, and contribute to thought leadership through customer engagements and industry events.
This role involves leading software development across AI and computer vision projects, from research through to deployment, within multidisciplinary teams. The engineer will contribute to product and service development, including AI Assurance, and provide technical leadership in design and architecture. Emphasis is placed on innovation, continuous improvement, and delivering engineering solutions for clients in complex technical domains.
