Artificial Intelligence Jobs

Faculty · Remote (UK)

Lead the design, build and deployment of production-grade ML systems for defence clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams, acting as a technical advisor and mentoring junior engineers. Requires on-site work with customers 2-4 days per week and eligibility for UK Security Clearance.

Helsing · London

Architect and scale the deep learning frameworks and distributed training infrastructure behind defence AI systems, extending PyTorch-based tooling and optimising GPU throughput. The role spans data strategy, storage and orchestration, working cross-functionally to maximise training efficiency and developer velocity.

CrowdStrike · Aarhus, Denmark

Owns major components of the Windows kernel-mode endpoint sensor, architecting and building anti-virus and EDR features that cut across file system, memory, process and networking subsystems. Works on cross-platform deliverables with shared components across Windows, Mac and Linux, leading projects from design through delivery and demo.

CrowdStrike · London

Builds and owns major components of the Falcon endpoint sensor, a Windows kernel-mode driver that observes system activity, detects malicious behaviour and provides on-box prevention plus telemetry to the cloud. Work spans OS internals such as file system, memory, process and networking, with cross-platform components shared across Windows, Mac and Linux.

Wayve · London

Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

Scale AI · London

Owns large enterprise AI projects end to end, from understanding customer pain points and defining requirements through development, testing and launch. Forward deploys with client teams to build bespoke GenAI applications on the Scale GenAI Platform, leading cross-functional groups and shaping product strategy with executives.

NVIDIA · United Kingdom

Serve as a trusted technical advisor to software solution providers, developers and startups across EMEA, driving adoption of NVIDIA's AI and computing platforms. The role involves accelerating workloads, advising on enablement resources, mapping the developer ecosystem and feeding field insights back to product and engineering teams. It blends deep technical work with commercial go-to-market and partner engagement.

NVIDIA · Switzerland

Serve as a trusted technical advisor for the healthcare and life sciences developer ecosystem, helping partners integrate NVIDIA's AI and computing stack into their products and pipelines. Work spans agentic AI, clinical documentation, trial matching and cross-specialty orchestration, with responsibility for mapping the European ecosystem and feeding field insights back to product and engineering teams.

Anthropic · London · £165,000 – £190,000 pa

Partner with founders and engineers to architect LLM solutions on the Claude Developer Platform, guiding startups from technical discovery through deployment. Win technical evaluations, build evaluation frameworks, and feed emerging use cases back to Product and Engineering. Requires travel to customer sites and startup events.

Morson Edge · West Yorkshire · £170,000 – £180,000 pa

A senior leadership role owning the data and AI strategy, roadmap and technical direction across the organisation. Day to day it spans hands-on work with generative AI, LLMs, RAG and agentic architectures, MLOps and data platform governance, plus building and leading a high-performing Data & AI team and partnering with Product, Engineering, Architecture and Security to scale prototypes into production.

eFinancialCareers · London

Leads the design, development and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate, defining the AI/ML roadmap while remaining hands-on. Owns the full model lifecycle from feature engineering and back-testing to deployment, monitoring and incident response, with models expected to be explainable and production-grade. Works closely with engineering, data platform and product teams, mentoring other data scientists with limited line management.

University of Southampton · Southampton · £46,970 – £49,798 pa

Lead a translational research project extracting structured clinical findings from electronic health records using open-source large language models, harmonising them to ontologies such as HPO, SNOMED CT and ICD-10. Develop reproducible LLM-based pipelines on high-performance computing, integrate clinical and genomic data for autoimmune disease diagnostics, and manage early career researchers within a multidisciplinary team.

Faculty · London

Scoping, building and delivering bespoke AI solutions for pharmaceutical and life sciences clients, managing individual work streams and translating operational requirements into user stories for engineering teams. Involves open-source analysis, workflow design and close collaboration with data science and ML experts, with a focus on high-stakes, user-centric decision-making.

Aioi Nissay Dowa Europe · Oxford · £81,322 – £112,488 pa

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.

Darktrace · Cambridge

Conducts independent and collaborative research across large language models, statistical methods and classical machine learning, prototyping ideas and implementing models into the wider software stack. Produces optimised solutions for latency and memory, including deployment on edge devices, working closely with software engineers and security analysts.