Future Tech Jobs
Future Tech Jobs
Design and develop novel Transformer and GNN architectures for a unified foundation model that interprets relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference optimization—on high-impact applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to advance graph learning and relational reasoning in enterprise AI.
Lead and scale Anthropic's Forward Deployed Engineering team by hiring top talent, overseeing technical delivery for strategic enterprise customers, and building repeatable playbooks for AI adoption. This role combines hands-on technical leadership with team development, shaping how organizations deploy Claude in production environments while feeding field insights back into product development.
Lead a distributed engineering team building critical connectivity infrastructure for AI agents, focusing on secure, scalable access to external systems via the MCP standard. Responsibilities include managing token management, OAuth flows, and proxy systems that power tool use across Anthropic's products. The role emphasizes operational rigor, cross-team alignment, and technical leadership in a high-trust, enterprise-focused environment.
Design and deploy AI systems for enterprise clients, translating business needs into technical architectures and production implementations. Work hands-on with code, evaluation frameworks, and integrations while guiding customers from prototype to scalable, reliable deployment. Collaborate across OpenAI teams to turn real-world deployment insights into product improvements and reusable solutions.
Design and deploy production AI systems for enterprise clients, guiding them from concept to scalable implementation. Work across the full technical stack to solve complex integration, reliability, and governance challenges while ensuring safety and measurable business impact. Translate real-world deployment experience into reusable tools and product improvements.
This role involves building and scaling the reliability foundations of a large-scale AI and GPU compute platform. You will define SRE frameworks, automation, and operational standards for model development and training infrastructure, ensuring high availability and performance. The position bridges AI research, cloud infrastructure, and production operations, with a focus on observability, incident response, and resilient system design.
Lead and deliver high-impact AI transformation projects for UK government and national security clients, bridging technical AI research with operational mission needs. Manage end-to-end project delivery, develop strategic proposals, and mentor cross-functional teams in a fast-evolving, high-stakes environment. Focus on responsible AI deployment, red teaming, and building trusted advisory relationships with senior stakeholders.
Design and build full-stack platforms that translate complex data science and AI insights into production-grade applications, with a focus on scalability and performance. Lead technical architecture, mentor engineers, and collaborate closely with data scientists and product managers in a regulated financial services context. Work across frontend and backend systems to deliver secure, reliable software solutions for high-impact clients.
Lead and develop a team of infrastructure engineers while driving technical strategy for systems supporting AI research and development. Focus on operational stability, automation, and infrastructure-as-code across bare metal GPU clusters, virtualized environments, and Kubernetes. Own incident response, capacity planning, and vendor relationships while fostering engineering growth through coaching and career development.
The Infrastructure Team Lead will lead a team of engineers while driving technical strategy across the full infrastructure stack, from bare metal GPU clusters to internal services. The role involves hands-on work with infrastructure-as-code (Terraform, Ansible, Helm), automation, and operational reliability, alongside coaching engineers and shaping career development. This position is central to scaling and stabilising systems that support AI research and development in a high-impact engineering environment.
This role involves developing and deploying advanced AI systems that enhance both seller operations and internal consultancy at Amazon. The scientist will design machine learning architectures—particularly using LLMs, generative AI, and optimization techniques—to solve complex marketplace challenges. The position emphasizes end-to-end innovation from research to production, with a focus on scalable, interpretable, and impactful AI solutions.
Design and implement high-performance machine learning models using C++, CUDA, and PyTorch, with a focus on GPU acceleration and advanced AI applications such as Transformers and computer vision. Work within a research-driven team to develop next-generation AI solutions for real-world deployment. The role involves low-level optimisation and close collaboration on cutting-edge algorithm development.
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 while guiding technical strategy and mentoring engineering teams in a high-performance environment focused on embodied AI for autonomous driving.
This role involves building and deploying AI systems to detect unsafe, unsuitable, or policy-violating content across digital advertising inventory. You'll develop low-latency, LLM-powered classification models that operate at internet scale, making real-time decisions across text, images, audio, and video to protect advertiser trust. The work combines frontier AI research with large-scale production engineering to combat evolving synthetic and adversarial content.
This role involves leading brand strategy and integrated marketing campaigns across trade and consumer channels, with a strong focus on AI-driven market research, content creation, and digital optimization. The Marketing Manager will use generative AI tools for insight generation, campaign efficiency, and content production while managing a small team and collaborating with sales and product teams. Key responsibilities include managing digital marketing platforms, executing product launches, and applying predictive analytics to inform commercial strategy.
