Artificial Intelligence Jobs

Wayve · London

Builds and operates backend services, APIs and data-processing workflows for a platform that deploys, runs and evaluates ML models over petabytes of driving data on large GPU fleets. Work spans model-execution workflows, versioned outputs, annotation and dataset-catalogue features, plus reliability, scheduling and observability across distributed systems.

Wayve · London

Owns reliability of large-scale GPU, Kubernetes and distributed AI training infrastructure, turning recurring operational problems into durable engineering solutions. Improves observability, automation, deployment safety, capacity planning and incident learning, and builds GitOps delivery with Argo CD or Flux. Works across AI Platform, Compute & Data Platform and Cloud Infrastructure teams.

Faculty · London

Technical leadership role owning delivery of complex machine learning and Generative AI projects for financial services clients, spanning LLM and agentic AI applications. Sets technical direction for the data science team, mentors and manages data scientists, leads bids and scoping, and acts as an external thought leader publishing and presenting at conferences.

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.

Capital One · Loughborough

Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. Set technical direction, manage projects, communicate with stakeholders and mentor junior team members, taking ideas from prototype to production in a hybrid Nottingham team.

Capital One · Lincoln

Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. The role involves setting technical direction, mentoring junior team members, and driving prototypes through to production in collaboration with business stakeholders.

Deerfoot Recruitment Solutions · Hertfordshire · £35,000 pa

Floating tester across a Data Platforms and Analytics function, covering middleware, data analytics, RPA and data platform teams. Uses AI tooling, including an in-house LLM-based tool, to generate and execute tests, then validates output. Tests an internally built AI agent, APIs, end-to-end data flows, Azure Synapse, Microsoft Fabric, Power BI, Tableau and UiPath RPA processes, writing SQL and lightweight Python for data reconciliation.

Harnham - Data and Analytics Recruitment · Nottingham · £60,000 – £80,000 pa

Build and scale an AI-powered enterprise platform, owning end-to-end product development across React, TypeScript, Python, AWS and PostgreSQL. Work spans secure authentication, third-party integrations, event-driven services and collaboration with AI specialists, within a senior, high-accountability engineering team.

Relation Therapeutics · London

Process and QC paired single-cell RNA-seq and scATAC-seq at scale, building Nextflow pipelines for custom combinatorial indexing chemistries and integrating multimodal datasets for GPU-accelerated model training. Partner with wet lab scientists and ML modellers to design evaluation frameworks that test whether models capture meaningful biology.

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.

Harnham - Data and Analytics Recruitment · London · £100,000 – £120,000 pa

Sits within a private equity firm's value creation function, designing and building scalable data platforms and architecture for portfolio companies. Works hands-on with SQL and Python to establish data engineering foundations for analytics and AI-ready environments, while advising C-suite stakeholders across varied data maturity levels and technology stacks.

eFinancialCareers · London · £90,000 – £120,000 pa

Hands-on technical leadership role owning AI solution design, architecture and delivery for large-scale, regulated environments, initially healthcare. Leads multidisciplinary engineering teams building production generative AI, LLM, RAG and agentic systems on Azure or AWS, while coaching engineers and managing client stakeholders.

Reed · Cambridge

Lead statistical and bioinformatics analysis projects, developing computational algorithms and applying machine learning to functional genomics research. Work with NGS, OMICS and high-throughput datasets alongside laboratory scientists, using Python, R or Julia and libraries such as TensorFlow and PyTorch. The role also involves mentoring and cross-functional collaboration in a multidisciplinary research team.

eFinancialCareers · Belfast

Hands-on player-manager role leading a growing Data & Analytics function, combining Power BI development, SQL analysis and AI exploration with stakeholder management and delivery leadership. You will build dashboards and semantic models, manage the Power BI environment and backlog, prototype HTML-based analytical applications, and apply generative AI and Copilot to improve reporting while coaching analysts and engineers.

ElevenLabs · United Kingdom

First dedicated analytics partner to Finance within a central Data team, owning revenue and ARR reconciliation, cohort and retention economics, and pricing experiments. Builds forecasting and scenario models used directly by FP&A for planning and board reporting, and partners with Analytics Engineering on the certified finance KPI layer. Requires reconciling data across Stripe, Salesforce and a dbt-modelled warehouse.