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.
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.
This role involves designing, developing, and evaluating machine learning models and analytical solutions within a collaborative R&D environment. The Data Scientist will bridge the gap between data science and product teams, translating AI strategies for stakeholders and integrating ML solutions into global product development. The position offers exposure to innovative technologies and real-world applications of AI/ML in an internationally used product suite.
A Principal Designer will lead the development of product and service design disciplines within Faculty’s Applied AI division, delivering high-impact client projects while building design capability from the ground up. The role combines strategic client engagement with executive-level consulting, shaping multidisciplinary teams and embedding human-centred design in AI solutions. This position bridges technical AI outputs with real-world commercial outcomes across government, finance, retail, and other sectors.
This role involves designing and deploying large-scale AI and HPC GPU infrastructure in collaboration with NVIDIA Cloud Partners, with a strong focus on datacentre power, cooling, and MEP integration. The Solutions Architect will guide customers through technical challenges, develop proofs of concept, and ensure efficient, scalable deployment of NVIDIA's hardware and software solutions. Key responsibilities include advising on datacentre best practices, troubleshooting infrastructure bottlenecks, and influencing future product development based on real-world deployment insights.
Leads AI transformation programmes for professional services firms, shaping go-to-market strategy and building C-suite relationships. Guides multidisciplinary teams in delivering production-grade AI solutions that automate complex knowledge work and drive operational efficiency. Combines deep technical understanding with commercial acumen to grow Faculty’s practice in a regulated, high-impact sector.
Design and implement GPU-accelerated solutions for hyperscaler environments, with a primary focus on Google Cloud Platform. Develop proof-of-concepts and optimize GenAI, machine learning, and data science workloads across training and inference pipelines. Collaborate with engineering, product, and sales teams to integrate NVIDIA technology into enterprise computing architectures and support developer adoption through technical engagement and performance optimization.
This role involves leading scientific research projects in applied physics and imaging technology, focusing on X-ray systems, optics, and AI-driven algorithm development. The scientist will use MATLAB extensively for data analysis, modelling, and creating advanced detection solutions. Work spans experimental research, machine learning, and cross-team collaboration to deliver real-world technological innovations.
Leads a team of data scientists to develop, deploy, and support AI solutions across public sector procurement projects, with a focus on generative AI, machine learning, and ethical AI practices. Manages end-to-end AI lifecycles including MLOps and GenAIOps, ensures technical quality, and advises on scalable, secure implementations in cloud environments like Azure or AWS. Engages in strategic planning, cross-functional collaboration, and innovation initiatives through an internal funding board.
This role involves working closely with government clients and partners to design and deploy AI-driven solutions using NVIDIA's hardware and software technologies. The Solution Architect will develop technical collateral, lead proof-of-concept initiatives, and guide field teams in implementing AI workflows across public sector challenges. A strong focus is placed on computer vision, generative AI, and MLOps, with an emphasis on translating mission goals into scalable technical strategies.
The role involves working closely with government clients and partners to design and deploy AI-driven solutions that address public sector challenges. You will develop technical strategies, create educational content, and support proofs of concept using NVIDIA's AI platforms. The position emphasizes hands-on technical leadership in computer vision, generative AI, and deep learning, with a focus on real-world deployment and cross-cultural collaboration.
This role involves working closely with government clients and partners to design and deploy AI solutions using NVIDIA's hardware and software technologies. The Solution Architect will develop technical strategies, create educational resources, support proofs of concept, and guide field deployments in areas like computer vision, generative AI, and digital twins. Emphasis is placed on translating public-sector challenges into scalable, AI-driven outcomes while advocating for product improvements based on real-world feedback.
This role involves working closely with government clients and internal teams to design and deploy AI-driven solutions that address public sector challenges. The Solution Architect will develop technical strategies, create educational resources, lead proof-of-concept initiatives, and support the implementation of AI workflows using NVIDIA's technologies. A strong focus is placed on computer vision, generative AI, and deep learning deployment in real-world government environments.
Design and demonstrate GPU-accelerated solutions leveraging NVIDIA and Google Cloud Platform (GCP) technologies, focusing on Generative AI and large-scale machine learning workloads. Engage with developers, data scientists, and technical leaders to optimize training and inference pipelines. Collaborate across engineering, product, and sales teams to integrate NVIDIA platforms into enterprise computing environments.
