Future Tech Jobs
Future Tech Jobs
Design and experiment with novel Transformer and GNN architectures to build a unified foundation model that understands relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference acceleration—enabling applications in forecasting, fraud detection, and recommendation systems. Collaborate with researchers and engineers to push the boundaries of relational reasoning in enterprise AI.
This role involves designing and experimenting with novel Transformer and Graph Neural Network (GNN) architectures to build a unified foundation model that understands relational databases and heterogeneous graphs. The engineer will work across the full ML lifecycle—from architecture design to inference acceleration—enabling applications in fraud detection, forecasting, and recommendation systems. Collaboration with researchers and engineers is central, with a focus on pushing beyond traditional single-table AI models.
Lead a team of data scientists focused on applying machine learning and large language models to cybersecurity challenges, including malware detection, behavioral threat analysis, and AI-driven security automation. Translate business needs into technical research objectives and collaborate across security, engineering, and product teams to deliver production ML systems at scale. Work on high-impact problems involving reverse engineering, decompilation, and adversarial dynamics within a platform processing trillions of daily events.
This role involves driving adoption of Databricks Lakebase, a fully managed Postgres service, by partnering with account executives and technical teams to position it for intelligent applications and modern operational data workloads. The specialist will lead sales cycles, conduct proofs of value, and enable field teams to sell Lakebase effectively to platform, data, and IT stakeholders. Success requires strategic engagement with high-value accounts, strong technical sales skills, and the ability to articulate business outcomes around cost, governance, and developer productivity.
This role involves working closely with sales teams and customers to design and demonstrate technical solutions using Databricks' Lakehouse Platform, with a focus on data and AI challenges in manufacturing, defence, and automotive sectors. The candidate will lead proof-of-concept projects, deliver technical workshops, and act as a trusted advisor to enterprise clients. Expertise in Generative AI, MLOps, and cloud-based data architectures is central to the position, along with strong customer-facing and mentoring skills.
This role involves leading and scaling the Engineering team, establishing strong engineering processes, and providing architectural oversight for a sophisticated AI-driven platform used by leading pharmaceutical companies. The position offers significant scope for impact and progression within a high-growth Series A business.
This role involves designing and implementing AI solutions to improve operational efficiency, defining LLM architecture, and building AI tools like assistants and workflow automation. You will work within an Azure cloud environment, collaborate with product teams, and act as a key partner to the Director of AI.
This role involves leading the annual business planning process, translating strategic priorities into actionable plans and performance metrics. The Business Planning Manager will drive performance management through KPIs, financial analysis, and forecasting, while producing insights and recommendations for senior leadership. They will collaborate across teams to align objectives, manage dependencies, and improve planning practices within Tesco Media’s data-driven environment.
The Client Director will lead senior client relationships and commercial agreements across key Tesco Group businesses, acting as a strategic partner to translate data and insight into actionable growth strategies. The role involves driving revenue performance, developing high-performing teams, and delivering integrated solutions in collaboration with Tesco and supplier partners. Success requires deep expertise in retail, FMCG, and customer data-driven decision-making within the UK market.
Lead the design and deployment of scalable AI and generative AI solutions, including LLM-based applications for enterprise search, document summarization, and conversational AI. Drive innovation through retrieval-augmented generation (RAG) architectures and mentor engineering teams in transformer models and prompt engineering. Collaborate across data, ML, and business teams to deliver measurable impact using cloud AI platforms and MLOps practices.
Lead the development of a scalable AI-driven system to analyze building data for housing providers, improving maintenance decisions and supporting decarbonisation. Own the full project lifecycle including data integration, machine learning model development, pipeline construction, and delivering actionable insights to stakeholders. Work embedded within an environmental tech company with university collaboration through the KTP programme.
This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.
This role involves working closely with customers in the Travel and Hospitality sector to understand their business challenges and design tailored cloud solutions using AWS technologies. The Solutions Architect acts as a trusted advisor, leading technical workshops, architecture reviews, and creating reference designs that leverage AI, generative AI, data analytics, and modern cloud patterns. The position emphasizes customer advocacy, technical education, and cross-team collaboration to drive innovation and long-term cloud adoption.
This role involves leading end-to-end testing strategies for AI and data-driven systems in a regulated enterprise environment, with a focus on validating AI models, including Generative AI and RAG solutions. The engineer will embed test automation within CI/CD pipelines, work across cloud-based services and APIs, and mentor teams in modern testing practices such as TDD and BDD. The position requires hands-on technical work alongside strategic oversight of quality assurance across digital platforms.
Build secure, auditable systems for handling lawful data access requests, translating legal and operational requirements into reliable technical workflows. Design backend services, data pipelines, and approval interfaces with strong privacy, least-privilege access, and full lifecycle auditability. Collaborate closely with Legal and Operations to improve accuracy, efficiency, and operator experience in high-stakes compliance processes.
