Future Tech Jobs
Future Tech Jobs
This role involves defining next-generation system architectures for NVIDIA's DPU and NIC technologies, focusing on cloud networking, security, virtualization, and orchestration. You'll lead end-to-end architectural design from hardware to application level, develop proof-of-concept prototypes, and collaborate with global teams and high-profile customers to shape future data center solutions.
Design and define next-generation system architectures for DPUs and NICs, spanning hardware to application layers with a focus on cloud networking, orchestration, and security. Lead architecture specifications and proof-of-concept development while collaborating globally with engineering and customer teams. Innovate across networking, virtualization, and SDN to shape the future of data center technologies.
This role involves serving as a technical advisor to enterprise customers adopting Anthropic's Claude AI, guiding them from initial evaluation through deployment. The Applied AI Architect will design scalable integration architectures, develop evaluation frameworks, and communicate technical concepts to both engineering teams and executives. Collaboration with Sales, Product, and Engineering teams is central to ensuring successful customer outcomes while upholding safety and reliability standards.
Build and maintain foundational systems for AI safety, oversight, and intervention mechanisms, focusing on detecting unwanted model behaviors and preventing misuse. Develop infrastructure for data management, evaluation systems, and tooling for human and agentic review while ensuring high operational reliability at scale. Work closely with cross-functional teams to implement robust, multi-layered defenses in a safety-first AI environment.
A Machine Learning Engineer will collaborate with simulation engineers, data scientists, and customers to solve complex physics and engineering challenges using AI. The role involves building scalable, reliable ML data pipelines, working with 3D point-cloud and mesh data, and translating R&D into reusable tools and products. Frequent customer site visits across multiple continents are expected to support on-site solution development and deployment.
Lead and shape research initiatives in machine learning for physics-based simulation, focusing on scalable and distributed training of foundation models. Translate research prototypes into robust, production-grade systems using cloud and HPC infrastructure, while mentoring junior engineers and guiding technical direction across the Research team.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy AI systems that solve real-world business problems. The role involves hands-on coding, system integration, and technical leadership to guide AI solutions from prototype to production, with a focus on reliability, safety, and measurable impact. The position requires deep technical expertise and strong collaboration with both customer teams and internal OpenAI groups.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy production-grade AI systems that solve high-impact business problems. The role involves hands-on coding, architecture design, integration, evaluation, and guiding technical decisions across safety, reliability, cost, and governance. Engineers will transition prototypes into scalable, reliable systems while contributing reusable tooling and influencing product development through real-world deployment insights.
This role involves designing, building, and validating integrations between partner technologies and the CrowdStrike Falcon Platform, while providing technical enablement and go-to-market support across Europe. The Solution Architect acts as a sales engineer for partners, delivering technical demos, proof-of-value exercises, and integration guidance. The position emphasizes deep technical collaboration with integration partners, automation of onboarding workflows, and the use of AI-assisted tools to improve efficiency in a cybersecurity context.
Lead a team building offline scene understanding models to evaluate and improve Wayve's autonomous driving systems. Develop robust, scalable models that leverage high-compute environments to generate counterfactual insights, assess driver behaviour, and inform model development. Work across UK and US teams to unify technical direction and accelerate the AV development loop through rigorous ML engineering and cross-functional collaboration.
This role involves advancing embodied AI for autonomous driving through research in world modeling, spatial intelligence, and scalable decision-making. You'll develop foundation models, reinforcement learning systems, and sim-to-real transfer techniques in a multidisciplinary environment. The work spans simulation, robotics, and real-world deployment, with a focus on long-horizon prediction and cross-embodiment learning.
This role involves conducting empirical research into the capabilities of specialised biological AI models, particularly in protein design and genomics, to assess their potential for misuse. The researcher will design experiments to evaluate in-silico predictions against real-world biological outcomes, test the effectiveness of technical safeguards, and translate findings into actionable insights for government and policy stakeholders. Work spans machine learning, computational biology, and biosecurity, requiring close collaboration with wet-lab scientists, AI developers, and security experts.
This role involves developing and optimizing machine learning systems for document classification and extraction, with a focus on fraud detection in identity verification. The engineer will work on production-scale LLM and traditional ML pipelines, improving accuracy and performance across global document types. Collaboration with cross-functional teams and mentorship of junior engineers are key aspects of the position.
This role involves deploying and optimising CrowdStrike’s AI-powered threat detection and response capabilities on the Falcon platform. The consultant will configure machine learning models, develop automation playbooks, integrate AI workflows with existing security tools, and provide technical guidance to customers and internal teams. The position requires deep expertise in AI/ML applications for cybersecurity, scripting with Falcon APIs, and troubleshooting across enterprise environments.
Design and build production-grade machine learning systems for document classification and extraction, focusing on high accuracy and scalability across global identity documents. Work with LLMs and traditional ML models, optimize inference pipelines, and collaborate with cross-functional teams to enhance fraud detection and customer onboarding. Emphasis on technical leadership, system reliability, and mentoring within a squad-based engineering culture.
