Artificial Intelligence Jobs

Faculty · London

Lead the design, build and deployment of production-grade machine learning systems for clients across pharma, healthcare and other sectors. Work spans architectural decisions, scalable infrastructure, MLOps standards and mentoring junior engineers, with a strong client-facing advisory element. Requires deep Python, TensorFlow or PyTorch, and cloud plus Docker/Kubernetes experience.

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

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.

Wayve · London

Builds and evolves the data pipeline and orchestration platform behind Wayve's autonomous driving data, revamping the existing Harness system and creating a new DAG-based workflow platform. Works with Python, Airflow/Dagster/Flyte, Ray or Spark and Kubernetes to run hundreds of parallel pipeline steps, batch inference and evaluations reliably at scale.

Amazon · London

Acts as a trusted technical advisor to AGI-DS scientists, translating complex research objectives into actionable ML/GenAI data collection requirements. Coordinates across teams to ensure delivery, owns customer scientist relationships, and monitors collection health metrics. Involves guiding on workflow feasibility, annotation scalability, and data collection best practices.

University of Warwick · Coventry · £21,805 pa

Develops medium-voltage solid-state transformer cells for hyperscale AI data centres and net-zero grids, tackling high-frequency power conversion, compact magnetic links and electrical-thermal degradation under high-dv/dt stress. Combines multi-physics finite-element modelling in ANSYS/COMSOL with experimental validation in a high-voltage power electronics lab, culminating in a scaled hardware prototype.

Amazon · London

Manage a London-based team of associates producing labelled speech and language data for Alexa and Amazon Echo ML systems. Day to day you assign work, monitor queue adherence, volume and quality, hire and train associates, build weekly schedules across competing workflows, and track quality and utilisation metrics. You liaise with program management and global operations leads on risk mitigation and drive process improvement using Kaizen, Six Sigma or lean methods.

Opus Recruitment Solutions · United Kingdom · £80,000 – £90,000 pa

Designs enterprise-scale AI, data and automation solutions, architecting generative and agentic AI, RAG, vector database and multi-agent systems across OpenAI, Azure OpenAI, Anthropic and Google Gemini. Runs customer discovery and solution-design workshops, creates reference architectures and roadmaps, and supports technical pre-sales, governance and Responsible AI. Remote-first with client site visits.

Harnham - Data and Analytics Recruitment · London · £100,000 – £140,000 pa

Build and lead multimodal AI applications spanning text, audio and video, including AI-generated avatars and automated content summarisation, within a growing AI team in a mature data function. The role involves translating business needs into scalable, production-deployed AI products and collaborating with a multidisciplinary team, with technical leadership duties at Lead level.

Harnham - Data and Analytics Recruitment · London · £75,000 – £80,000 pa

Hands-on role owning the modelled data layer, building staging, mart and analytics models in dbt and BigQuery that power reporting, self-service analytics and data activation. Works closely with Data Engineering and analysts to evolve the warehouse into a scalable global platform, with dbt testing, lineage, documentation and Looker/LookML development.

TRIA · Bristol · £500 – £600 pd

Eight-week proof-of-concept contract assessing how AI and LLMs can automate a complex data transformation process, reducing manual intervention. The role involves rapid PoCs on real datasets, automating mapping, standardisation, matching and exception handling, and designing auditable workflows. Requires strong ETL skills with tools such as Power Query, Alteryx, OpenRefine and Microsoft Fabric, plus stakeholder engagement.

King's College London · London · £45,031 – £52,514 pa

Designs, builds and evaluates AI-enabled evidence synthesis tools and pipelines for the METIUS programme, writing production-quality Python code and onboarding consortium partners. Runs methodological and evaluation studies on the reliability and usability of AI-assisted synthesis methods, publishing the results, and contributes to the Solace-AI project on climate-health emergencies. Works alongside software developers, data scientists and evidence synthesis specialists.

Experis · London · £70,000 – £110,000 pa

Hands-on leadership role taking AI solutions from proof of concept to secure, production-grade deployments in regulated Security & Justice environments. Involves designing end-to-end AI architectures, leading multidisciplinary teams, shaping technical roadmaps and ensuring governance and security compliance across LLM, RAG and MLOps workstreams.

Adecco · London · £700 – £800 pd

Drives enterprise-wide AI adoption within an EMEA Data Management Office, bridging business needs and AI capabilities. Develops use cases, playbooks and prompt libraries, runs training and champion networks, and tracks adoption, value and ROI. Hybrid role in London, three days per week on site.

Databricks · London

Customer-facing, billable engineering role owning architecture and design decisions while building production-grade data and AI systems on the Databricks platform. Involves embedding with client teams, integrating with their systems, and delivering end-to-end pipelines, ML/AI models and user-facing applications, with around 20% travel to customer sites.