Artificial Intelligence Jobs

Local Pensions Partnership Administration · Preston · £90,000 – £100,000 pa

Lead AI strategy, governance and delivery across a major UK pension administration organisation, working with the CTO and executive team to identify and scale AI opportunities. Establish responsible AI frameworks, build and manage a specialist AI team, and oversee adoption of tools such as Microsoft Copilot, Civica UPM and UiPath. The role combines strategic leadership, risk assurance and supplier engagement to drive measurable service improvements.

eFinancialCareers · London

Leads a global legal and professional services firm's AI and data agenda, translating strategy into a delivery programme that moves initiatives from experimentation to sustainable adoption. Works across legal, fiduciary and business services divisions on productivity, decision-making and client outcomes, reporting to the Director of Service Innovation and managing AI and data delivery teams through matrix leadership.

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.

Harnham - Data and Analytics Recruitment · London · £120,000 – £150,000 pa

Lead and build a data science function within a fintech, owning strategy across risk, affordability and lending decisioning. Design, build and deploy machine learning models using credit risk, Open Banking and customer data, working with Product, Engineering and Credit Risk teams. Requires hands-on Python, SQL and MLOps experience plus credit risk modelling in UK consumer lending.

Isomorphic Labs · Cambridge, United States

Lead the safety assessment strategy for drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments for small molecules and biologics. Partner with machine learning researchers to build predictive toxicology models and manage CRO relationships for outsourced wet-lab data generation, while mentoring junior scientists.

Isomorphic Labs · Cambridge, United States

Lead and execute the translational medicine strategy across oncology programs, ensuring clinical biomarker assay readiness and data delivery to inform mechanism of action, resistance and future indications. Serve as a core program team member and cancer biology expert, collaborating with AI and computational biology teams to build innovative biomarker analysis tools and advance companion diagnostics.

Multiverse · London

Bridges People strategy with hands-on technical product management, building an AI-native People function from the ground up. Owns the vision, strategy and quarterly roadmap for internal People Ops technology, covering core HR systems, integrations, data flows, identity and automation for ~1000 employees. Requires systems thinking and influence across People, Engineering, Security, Compliance, Legal and Analytics.

Synthesia · London

Owns the end-to-end roadmap for enterprise governance, content lifecycle and admin tooling, from workspace setup through compliance controls. Works closely with engineering, design, Solutions, CS and Legal on deal-critical features, defining adoption and escalation metrics. London-anchored with in-person time and regular travel.

Noir · Abingdon · US$170,000 – US$195,000 pa

Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI (LLMs, RAG, AI agents) for a specialised luxury and wealth intelligence market. The role blends hands-on engineering with founder-level strategy and equity.

Noir · London · £160,000 – £180,000 pa

Take full ownership of the technology function at an early-stage AI venture, making key architectural decisions and building a founding engineering team. The platform combines proprietary data, real-time insights and advanced AI, with work spanning LLMs, RAG pipelines, AI agents, data infrastructure and cloud architecture. It is a hands-on founder role rather than a traditional management position.

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.

PhysicsX · Singapore

Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.

Databricks · London

Lead a team of Enterprise Named and Strategic Account Executives covering Telco and Utilities in UKI, owning team quota and growing platform consumption. You set territory plans, quotas and patches, drive forecast accuracy and partner with cross-functional teams on a full revenue and customer success process. Reports to the RVP, Enterprise.

Luminance · London

This is a fantastic opportunity to join Luminance, the pioneer of Legal-Grade™ AI for enterprise. Backed by internationally renowned VCs and named in both the Forbes AI 50 list of ‘Most Promising Private AI Companies in the World’ and Inc....

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.