Artificial Intelligence Jobs

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.

Isomorphic Labs · Cambridge, United States

Lead medicinal chemistry on drug discovery projects from initiation to clinical candidate selection, either as Project Lead or Medicinal Chemistry Lead. Partner closely with ML scientists to refine the AI drug design platform, manage CRO resources, and generate IP. Some roles include line managing 2-4 chemists.

Isomorphic Labs · Cambridge, United States

Lead computational drug design programs from initiation through to clinical candidate selection, applying AI-first approaches and shaping the company's ML drug design engine. Work cross-functionally with ML, biology and chemistry teams, with optional people management of 2-3 computational chemists.

CrowdStrike · London

Internship on CrowdStrike's Technical Analysis Cell, researching nation-state and criminal intrusions through reverse engineering of malware and tooling. The intern documents findings, builds automation for malware analysis, creates host- and network-based detection signatures, and produces threat intelligence reporting for varied audiences.

Darktrace · London

Deploys, integrates and optimises AI-driven security technology across network, cloud, OT and email environments for post-sales customers. Handles deployment projects against SLOs, resolves support tickets and acts as a trusted advisor on security infrastructure design, liaising with sales, customer success and operations.

Darktrace · Cambridge

Acts as the go-to authority in a chosen reliability specialism—observability, performance engineering, data infrastructure, security-focused SRE or network reliability—defining standards and best practices across SRE, Platform Engineering and DevSecOps. Builds tooling and automation, leads deep-dive investigations into systemic issues, and contributes to incident response and on-call rotations in a cloud-native, Kubernetes-based environment.

Helical · London

Provide scientific leadership across model evaluation and applied use cases, ensuring foundation models stay grounded in drug development and translational research challenges. Act as a key scientific partner to the research team, mentor junior colleagues, and work with Product and Business Development to turn biology and ML into customer-facing deliverables.

EMBS Engineering · London · £75,000 – £85,000 pa

Lead a team of AI developers while remaining hands-on, building enterprise-grade Generative and Agentic AI applications for a financial services client. Work spans Python and Java services, FastAPI APIs, LLM integrations, RAG architectures and agent-based workflows on AWS Bedrock, AgentCore and EKS, plus CI/CD and DevOps. Also involves setting engineering standards and mentoring within a consultancy team.

Helical · London

Lead scientific evaluation and applied use of foundation models in drug discovery and translational research. Act as a senior individual contributor and scientific partner, mentoring junior colleagues while working with Product and Business Development to turn biology and ML into customer-facing deliverables as the team scales.

Helsing · Barcelona, Spain

PhD research internship tackling open problems in spatial perception and localisation within the Spatial Intelligence Team. You survey and prototype state-of-the-art methods for scene matching, SLAM/VIO and 3D reconstruction, benchmarking ideas against real-world data and compute constraints, and report findings to a Europe-distributed team.

Entrust · London

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines, and mentors engineers within a squad-based team.

Entrust · London

Owns a core area of the document verification platform, setting strategy and roadmap for identity document checks used in onboarding and account opening. Works with Engineering, AI/ML, Data Science, Design, Growth and Compliance to improve verification accuracy, conversion, operational efficiency and fraud prevention, using experimentation and analytics.

OpenAI · London

Hands-on engineering partner to international public-sector customers, delivering scoped GenAI and agentic use cases from mission need through architecture, evaluations, production and handoff. Works with government agencies, systems integrators and cloud providers on data residency, sovereign and regulated deployments, building prototypes on model APIs and Codex while feeding insights back to Product and Research.

Amazon · London

Owns the education-specific generative AI go-to-market for AWS, building co-sell strategies with model providers and leading Innovation Acceleration engagements for EdTech firms, universities and education ministries. Engages senior leaders such as founders, presidents, CIOs and government officials to drive net-new GenAI workloads on Amazon Bedrock, working with Solutions Architects, the GenAI Innovation Center and partner teams. Requires 25-35% travel and global customer coverage.

OpenAI · London

Lead a team of senior Applied AI Architects acting as the technical "CTO of the book of business" for OpenAI's largest enterprise customers across North EMEA. Own technical account strategy, resource allocation and paths to production across ChatGPT Enterprise, the API, Codex and agentic solutions, while coaching the team and serving as an executive technical sponsor.

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.