Artificial Intelligence Jobs

Luminance · Cambridge

Joins a new Quality team to build and maintain a state-of-the-art QA process, writing end-to-end tests with Cucumber, Cypress and Playwright and investigating defects to prevent recurrence. Acts as the link between Development and Product, formalising specifications into testable units and driving the shift toward automation as standard, including release quality metrics.

Hyre Ai · London · £50,000 – £60,000 pa

Design and evolve production multi-agent systems using Anthropic, OpenAI and Perplexity models on AWS, extending the company's MCP server with new tools. Build the eval and observability layer with golden datasets, regression suites and LLM-as-judge, own AWS infrastructure (ECS Fargate, Lambda, Step Functions, Bedrock) and guard against prompt injection and PII leakage. Set technical direction and mentor engineers.

Faculty · London

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves technical scoping, architectural decisions, and advising stakeholders, with reusable infrastructure work alongside engineers and data scientists.

Wayve · London

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing expert challenge and oversight across AI/ML, systems, validation and operational safety. Requires deep safety-case and systems engineering expertise in safety-critical domains.

Emponics · Bristol · £80,000 – £130,000 pa

This role involves owning the data infrastructure for AI deployments, integrating AI solutions into business systems, and ensuring reliable and scalable production-grade pipelines. You will work closely with AI strategists to take prototypes to production, manage data models, and troubleshoot integration issues.

Ocado · Erith

Lead a team of engineers, technicians and trainees at an automated Customer Fulfilment Centre, allocating daily workload, assessing capabilities and handling disciplinary matters. Requires hands-on mechanical and electrical engineering competence plus familiarity with MHE systems and computerised maintenance management. The role follows 12-hour shifts across days, nights and weekends to support a 24/7 operation.

Faculty · Remote (UK)

Owns end-to-end delivery of AI transformation programmes for UK Defence clients, from scoping and planning through implementation and user adoption. Acts as the link between customers and data scientists, translating mission challenges into AI solutions while managing senior stakeholders and growing commercial opportunities. Requires UK Security Clearance eligibility and 2-4 days per week on client sites.

OpenAI · London

Owns a small portfolio of complex enterprise accounts, driving the full sales cycle from pipeline generation to deployment of AI products. Partners with researchers, engineers and solution strategists on customer programs while carrying a consumption revenue target and forecasting. Requires deep technical fluency and executive-level relationship building.

VIQU IT Recruitment · London · £50,000 – £70,000 pa

Hands-on engineering role deploying and configuring a platform on Palantir Foundry for large industrial enterprise customers. You will build data pipelines, transformations and integrations, connect customer data sources, and work directly with client stakeholders to get deployments live, supported by senior FDEs and repeatable patterns.

Sanderson · London · £550 – £700 pd

Builds, deploys and maintains machine learning models and end-to-end ML pipelines in a modern cloud environment, writing production-quality Python and SQL. Works with data scientists, analysts and engineers to take AI products from proof of concept to production, including NLP and large language model work, plus monitoring and documentation.

Harnham - Data and Analytics Recruitment · London · £80,000 – £85,000 pa

Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.

Relation Therapeutics · London

Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.

eFinancialCareers · London

Build AI tools, LLMs and intelligent automation while developing data infrastructure and analytical solutions in Python and SQL. Create dashboards and portfolio analytics to support investment decisions, working directly with the CIO, CFO and senior leadership in a privately owned investment family office. The role offers autonomy to take technology initiatives from concept through to delivery.

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.

Faculty · Remote (UK)

Deliver bespoke, production-grade machine learning systems for defence clients, covering the full ML lifecycle from architecture and scoping to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, splitting time between client sites and remote work.