Artificial Intelligence Jobs

Carrington Recruitment Solutions · Leeds · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI-native edge using GenAI tooling. Mainly remote with occasional light travel to Leeds and other offices.

Carrington Recruitment Solutions · Manchester · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Works with C#, .NET, Python, Azure PaaS, SharePoint and React, collaborating with Product and Architecture, with an AI-native edge using GenAI tooling. Mainly remote with occasional Manchester office visits.

PhysicsX · Singapore

Customer-facing engineering role building and deploying applications that put physics AI models into production for industrial clients. You will work directly with customers, data scientists and ML engineers, prototyping tools, iterating on user feedback, and building Python FastAPI microservices deployed on Kubernetes, Terraform and AWS/Azure.

Thought Machine · London

Owns complex, ambiguous technical challenges end-to-end, shaping long-term architecture and engineering standards across cloud-native banking platforms. Acts as a link between senior leadership and engineering teams, driving systemic change, mentoring senior engineers, and improving production operations. Uses Go/Python and AI tooling to scale developer velocity.

Thought Machine · London

Guardian of mission-critical production infrastructure powering core banking and payments platforms for major financial institutions. Involves automating fleet management, designing disaster recovery and capacity planning, participating in a global on-call rotation, and mentoring engineers while working with senior stakeholders and SaaS customers.

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.

Amazon · London

Lead teams of technicians running AWS data centre operations, owning the full infrastructure lifecycle from rack installation and break-fix maintenance to decommissioning. The role spans building new sites, vendor management, health and safety compliance, and adopting high-density GPU, AI accelerator and liquid-cooling technologies, with a focus on automation and operational metrics.

VIQU IT · Cornhill, Greater London · £90,000 – £95,000 pa

Owns the end-to-end architecture of an enterprise AI platform spanning Azure and AWS, covering ML training, model hosting, MLOps and Generative AI. Defines patterns for LLMs, RAG, vector search and agent frameworks, evaluates tooling, and provides technical direction to ML and platform engineers while embedding security, governance and regulatory requirements.

Anthropic · London · £195,000 – £245,000 pa

This role involves conducting empirical economic research to understand AI's impact on labor markets, productivity, and economic transformation across a specific region. The economist will develop and expand the Anthropic Economic Index using novel measurement systems like Clio, applying advanced econometric and machine learning methods. They will collaborate with governments, academia, and policy institutions to translate research into actionable insights and influence both public policy and internal business decisions.

Databricks · United Kingdom

Customer-facing technical authority on Generative AI, LLMs and applied ML for digital-native and startup accounts across EMEA. Shapes architectures, builds hands-on proofs of concept and reference implementations on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog), and leads fine-tuning and evaluation engagements on open models. Also mentors the field engineering organisation and represents the company externally through talks and blogs.

Wayve · London

Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.

VIQU IT · London · £75,000 – £80,000 pa

Designs and deploys AI/ML models for forecasting, propensity, churn and customer segmentation, owning end-to-end workflows from feature creation to ML Ops deployment and monitoring. Works hands-on across multiple products, architecting bespoke datasets and coaching junior data scientists in a cloud-native, AI-first SaaS team.

Faculty · London

Owns and develops product and service design as a core discipline within the Applied AI division, delivering billable client engagements and anchoring project deliverables. Builds executive relationships with client leadership, defines skill and progression frameworks, and partners with business development to shape multidisciplinary teams. Balances strategic delivery with building an entrepreneurial design function.

Wayve · London

Works at the boundary between onboard software and vehicle hardware, bringing up new vehicle platforms on benches, HiL systems and vehicles, including at international test locations. Builds and maintains vehicle-facing components and shared frameworks in C++, Python or Rust on Linux-based robotic and automotive systems using ROS2, CAN and Automotive Ethernet, with diagnostics, tooling and documentation for long-term supportability.

Relation Therapeutics · London

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction, generalisation and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling including agentic workflows.