Artificial Intelligence Jobs

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.

Thought Machine · London

Owns and resolves high-priority incidents across hosted SaaS and bank-hosted Vault deployments, acting as a domain expert in Vault Core. Builds tooling, dashboards and automation to improve observability and support delivery, partnering with Engineering and Product on platform stability. Leads escalations end-to-end and mentors across client, product and engineering boundaries.

Thought Machine · London

Technical Programme Managers own the delivery of complex, multi-team engineering programmes, from planning and milestones through to coordination and stakeholder communication. The role requires hands-on understanding of microservice stacks such as Kubernetes, Kafka and AWS/GCP, and involves driving continuous improvement across a fast-paced engineering organisation.

NVIDIA · Cambridge

Serve as the primary technical contact for academic and research partners, driving adoption of NVIDIA's accelerated computing and AI stack. Work directly with labs and faculty on large language model workloads, integrating frameworks and libraries into research projects. Deliver hands-on training, workshops and lectures, and track emerging research trends to shape prototype solutions.

NVIDIA · Reading

Acts as the primary technical contact for academic and research partners, embedding NVIDIA's frameworks and software stack into large-scale AI and HPC workloads. Drives joint research projects, delivers workshops and trainings, and feeds researcher needs back to engineering. Requires deep LLM lifecycle expertise across multi-node systems and involves around 30% travel.

eFinancialCareers · London

Engineering-led security role building defences against AI-driven threats, spanning AI-assisted vulnerability management, exploit validation, and security architecture for agentic AI deployed across a global bank. Works in small, high-autonomy teams shipping production tooling, with paths into offensive security, AI platform assurance, CISO AI services, or cyber security operations.

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

Wayve · London

Hands-on role optimising inference for edge accelerators and GPUs so large transformer models run efficiently on low-cost, low-power in-vehicle compute. You'll profile model graphs, compiler/runtime behaviour and kernel execution, implement optimisations like fusion, scheduling and custom kernels, and build benchmarking and regression tests across NVIDIA Orin/Thor and Qualcomm targets, working closely with model, platform and deployment teams.

Copello · Bristol · £80,000 – £900,000 pa

Take technical ownership of FPGA and programmable logic design for advanced gimbal payload systems, covering video capture and processing, sensor and high-speed serial interfaces, and real-time pointing and stabilisation control. Work spans RTL design, simulation, synthesis, timing closure and hardware bring-up, taking in-house boards from prototype to qualified production while mentoring other engineers.

Faculty · London

Lead and grow a banking practice within an applied AI consultancy, shaping go-to-market strategy and building relationships with C-suite banking leaders. You will drive complex AI transformation programmes from strategy through software delivery, generate revenue through pitches and demos, and mentor multidisciplinary teams. The role blends commercial ownership with deep sector expertise in a regulated industry.

83zero · London · £75,000 – £90,000 pa

Design and build intelligent Salesforce solutions, integrating AI capabilities such as Einstein, Prompt Builder and Agentforce into platforms and workflows. Work with business, product and engineering teams to translate complex requirements into scalable technical solutions, optimising data models, automation and integrations with enterprise systems using Apex, LWC and APIs.

ElevenLabs · United Kingdom

Build and operate production-grade abuse detection and guardrail systems, focusing on free-tier abuse, fraud, and bot farming across a multimodal platform. Own the safety infrastructure end to end, from architecture and APIs to data pipelines, monitoring, and SLIs/SLOs, working with ML and full-stack engineers to move research models into production.

Isomorphic Labs · London

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.

Wayve · London

Post-train, distill and evaluate GAIA-family large video diffusion world models for synthetic driving data, covering embodiment and pose transfer. Own large-scale GPU generation pipelines and land synthetic data into the driving-model training stack, working between ML research and platform engineering.