Future Tech Jobs
Future Tech Jobs
Design and develop novel Transformer and GNN architectures for a unified foundation model that understands relational databases and heterogeneous graphs. Work across the full ML lifecycle—from research to production deployment—on applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to push the boundaries of relational reasoning in enterprise AI.
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.
This role involves developing computer vision and predictive maintenance systems that integrate inspection imagery with equipment operating history and physics-based data to forecast component lifespan. The data scientist will work directly with industrial customers to build robust, interpretable models for high-stakes engineering environments, emphasizing model transparency and real-world deployment. The position focuses on creating scalable, production-grade ML pipelines that support decision-making in asset-intensive industries.
Develop and validate high-fidelity multiphase CFD models for industrial applications in bioprocess and chemical engineering, integrating with AI-driven simulation workflows. Work across the full simulation lifecycle—from CAD and meshing to solver development, HPC execution, and experimental validation—while collaborating directly with clients to solve complex engineering challenges. Focus on scalable automation, surrogate modelling, and data pipelines to enable AI-enhanced design optimisation.
Leads the design and implementation of high-rigor machine learning and analytical systems across a regulated financial services environment. Focuses on production-grade models for anomaly detection, forecasting, and behavioral signals, ensuring reliability, explainability, and regulatory compliance. Works closely with engineering and product teams to drive models from concept to operation and provides technical leadership in complex, data-intensive scenarios.
This role involves leading end-to-end technical program delivery for AI deployments within UK public sector and defence organisations. The individual will act as a bridge between Cohere’s advanced AI capabilities and government stakeholders, managing complex procurement, security, compliance, and integration requirements. Success requires navigating air-gapped environments, high-stakes governance, and multi-team coordination to ensure responsible, secure, and scalable AI adoption.
The role involves designing and improving data workflows for risk analytics, focusing on market data ingestion, integration, and validation. The analyst will translate business needs into technical specifications, troubleshoot data issues using SQL and Python, and support scalable delivery of risk analytics solutions. Collaboration across engineering, data, and client-facing teams is central to the position.
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 large-scale deployment of voice assistants, ensuring client success through strategic oversight, quality control, and performance tracking. The strategist acts as the primary point of contact, translating client needs into technical execution while driving adoption and expansion. They work cross-functionally to refine agent design and deliver transformative customer service automation solutions.
Lead the development of AI-powered products by shaping product management standards and delivering high-impact client solutions. Work across multidisciplinary teams to translate advanced AI models into durable, user-centric software, while building organisational capability in product practice. Advise executives on technology adoption and drive commercial outcomes through strategic product leadership.
Design and build distributed failure detection, tracing, and observability systems to ensure reliable, efficient training of large-scale AI models. Work closely with research and infrastructure teams to debug and optimize performance across custom supercomputing environments. Focus on low-level systems, hardware awareness, and real-time insights into complex distributed workloads.
This role involves leading the strategic development and delivery of AI transformation programmes for enterprise clients across BFSI, Energy, Utilities, and Diversified Industries. The AI Practice Lead will define AI strategies, develop market-ready offerings, and provide technical leadership across Generative AI, LLMs, RAG, and enterprise data platforms. They will mentor cross-functional teams, drive innovation, and ensure high-impact outcomes through hands-on architectural guidance and governance of complex AI initiatives.
This role involves designing and maintaining a modern, AI-powered revenue operations stack using Salesforce as a core platform. You'll build intelligent automations with Flows and Apex, develop custom integrations including AI tooling and MCP servers, and create SQL-based data pipelines for reporting. The role bridges Salesforce administration and backend development, working closely with engineering to implement scalable GTM systems that reflect real business workflows.
The role involves designing and developing end-to-end systems using machine learning, deep learning, generative AI, and other advanced technologies to solve complex, real-world problems. Interns will create algorithms, deploy solutions into production, and collaborate with Amazon scientists. The position offers hands-on experience in a customer-focused environment with opportunities to publish research and contribute to impactful projects.
This role involves advancing large language model (LLM) development through research and experimentation, focusing on architecture design, optimization, and scaling. The researcher will work on improving model intelligence and efficiency, contributing to both training infrastructure and inference systems. Based in London with a hybrid work model, the position emphasizes hands-on empirical work and collaboration within a cutting-edge AI research environment.
