Artificial Intelligence Jobs

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

Anthropic · London

Leads multi-hundred megawatt power procurement and energy markets strategy for AI datacentre expansion across multiple EU jurisdictions. Builds relationships with TSOs, DSOs, regulators and ACER, structures PPAs and behind-the-meter solutions, and translates grid constraints into capacity acceleration plans.

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.

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.

Faculty · London

Lead the scientific direction and architectural rigour of upstream AI safety and evaluation standards, partnering directly with Frontier Labs. Design novel experiment frameworks, mentor data scientists, and translate complex challenges into rigorous scientific frameworks for high-stakes client engagements. Combines deep research with commercial strategy and thought leadership.

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.

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.

Morson Edge · Heathrow, United States · £625 – £650 pd

Lead data and AI engineering work for a major airline, focused on AWS, Snowflake and CI/CD pipelines. The role is inside IR35 and requires one to two days per week on-site at Heathrow, with the remainder likely remote. It is a long-term contract position.

CrowdStrike · United Kingdom

Lead a team of three data scientists at the intersection of machine learning, big data and cybersecurity, setting technical standards and driving strategy for threat detection and agentic AI systems. Work spans research through production deployment, using CrowdStrike's large-scale behavioural and malware data, while mentoring the team and partnering with security research, engineering and product.

CrowdStrike · Spain

Leads a team of three data scientists building machine learning and agentic AI systems for threat detection, malware analysis and security automation. Owns technical strategy, roadmaps and production deployment while mentoring staff and partnering with security research, engineering and product teams.

Wayve · London

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving experience. Own the loop end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

Data Idols · London · £105,000 – £120,000 pa

Hands-on technical leadership role driving the design, development and deployment of AI, Machine Learning and Generative AI solutions, including LLMs and agentic AI. Partners with business and technology stakeholders to identify high-value use cases, prototype rapidly and take solutions through to production, while shaping the AI technical roadmap and engineering best practices.

Databricks · London

Lead a delivery team of 8+ engineers building and productionising data and AI solutions on the Databricks platform for enterprise customers. The role blends hands-on technical oversight of Spark, Python/Scala, cloud and MLOps architectures with professional services delivery metrics, hiring and coaching. Hybrid working in London, with accountability for bookings, revenue, margin and customer satisfaction.

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 · £100,000 – £130,000 pa

Design, build and operate LLM-powered systems, taking AI products from experimentation to reliable production deployment. Work spans multi-step agent workflows, production-scale RAG, evaluation frameworks and retrieval pipelines, with mentoring duties at Lead level. Python and cloud infrastructure underpin the full development lifecycle.