Artificial Intelligence Jobs

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.

Thought Machine · Singapore

Provides 24/7 global client support for a cloud-native core banking platform, triaging technical issues, reviewing logs, traces and observability dashboards, and performing initial diagnostics. Also provisions cloud infrastructure, runs product upgrades and releases, and works with L3 engineering and client success teams on root cause analysis.

Wayve · London

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving experience. Own the loop end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

Wayve · London

Develops embedded software connecting an AI Driver to vehicle steering, braking and propulsion systems, working hands-on with benches and vehicles. Involves MATLAB/Simulink development, drive-by-wire actuation logic, CAN/CAN-FD diagnostics, OTA updates and ADAS/HMI interfaces, collaborating with OEMs, suppliers and controls engineers.

OpenAI · London

Builds and scales the infrastructure that trains and deploys AI agents, spanning a novel in-house container orchestration platform, FastAPI and gRPC APIs, and Terraform-managed cloud systems. Works closely with researchers on large-scale training runs and with product teams launching agentic products to hundreds of millions of users.

Nordson · Colchester

Lead and unify a globally distributed software engineering organisation across Colchester, Feldkirchen, Bangalore and remote teams in Europe and Asia. The role balances customer-specific delivery with strategic product roadmaps, architectural modernisation and the adoption of AI both in engineering processes and in X-ray, acoustic and optical inspection products.

OpenAI · London

Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training workloads, identifying slow or faulty nodes and surfacing performance bottlenecks. Work deep in the stack across collective communication, parallelism, fault tolerance, and observability, collaborating with systems, infrastructure, and research teams to evolve the training platform.

Harnham - Data and Analytics Recruitment · United States · US$200,000 – US$225,000 pa

Build and own core platform capabilities including application infrastructure, APIs and shared services, developing full stack applications in Python, React and TypeScript. Surface machine learning and predictive analytics insights through intuitive interfaces and integrate AI/LLM workflows into production, working in a small innovation team with significant architectural ownership.

Scale AI · London

Builds and scales backend systems and APIs that bring large-scale generative AI products to production for enterprise customers. Work spans distributed data systems, model serving, deployment pipelines, and cloud infrastructure across AWS, Azure, or GCP, in close collaboration with ML and product teams. The role centres on reliability, latency, throughput and cost optimisation in hybrid and multi-cloud environments.

Synthesia · Seattle, United States · US$200,000 pa

Builds and operates core enterprise platform systems, ensuring security, reliability and scalability for large customers, and contributes to a new API suite exposing Avatar technology to external creative tools. Owns multi-month, cross-team projects, translating business and regulatory requirements into scalable designs, and works with Python, React and AWS alongside product, security, legal and infrastructure partners.

Faculty · London

Lead the technical direction and delivery of complex AI projects for enterprise clients in financial and professional services, acting as primary technical authority from discovery to production. Balance hands-on full-stack work in Python and TypeScript/React with mentoring a squad of engineers and shaping reusable architecture. Distinct for its client-facing, highly regulated context and emphasis on safe, responsible AI deployment.

PhysicsX · New York, United States · US$150,000 – US$190,000 pa

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.

PhysicsX · New York, United States · US$200,000 – US$300,000 pa

Partners with engineering teams to embed security into CI/CD pipelines, lead threat modeling and secure design reviews for web apps, APIs and cloud services, and manage the product vulnerability lifecycle. Also drives secure coding standards, delivers training, and engages with customers during security reviews, with a strong DevSecOps and application security focus.

The University of Manchester · Manchester · £48,337 – £59,390 pa

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

University of Oxford · Oxford · £39,424 – £43,984 pa

Develops 3D reconstruction and multi-view data fusion methods for neonatal cranial ultrasound, validating them on data from the neonatal intensive care unit. Works at the intersection of 3D computer vision, neural rendering and medical image analysis, including physics-informed rendering models for view-dependent acoustic appearance. Based in a multidisciplinary lab alongside deep learning researchers, software engineers and neonatologists.