575 jobs for “data mining”
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.
Harnham - Data and Analytics Recruitment London £80,000 pa
Builds internal AI agents, tools and prototypes within a small central technical team, turning complex group data into usable products at speed. Work spans Python, TypeScript and SQL, modernising legacy systems, wrapping systems in scalable APIs and contributing to shared data and entity platforms, with weekly demonstrable output.
Databricks London
Founding backend engineer role building Lakebase, a managed Postgres transactional layer for the lakehouse, across teams covering platform reliability, a central control plane, and a high-throughput network proxy handling Postgres, HTTP, WebSockets and Data API traffic. Work spans distributed systems, at-scale service architecture, observability, SLI/SLO definition and AI-powered automation, with services on AWS S3, GCS and Azure Blob Store.
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.
OpenAI London
Builds internal tools and data pipelines for lawful data access request workflows and Legal Operations, covering intake, scoping, authorized retrieval, review and audit. Involves backend services, sensitive-data handling, least-privilege access, audit trails and responsible automation, working closely with Legal, Privacy and Security stakeholders.
Scale AI London
Leads an infrastructure engineering team owning the full deployment lifecycle of AI products in live customer environments, from rollout to long-term operational health. Sets the infrastructure roadmap, SLAs/SLOs, and drives backend work on AI agents, evaluation tooling and automation across Kubernetes, Terraform and CI/CD. Bridges AI research and production while working cross-functionally with customers, GTM, product and security.
Scale AI London
New grad engineers own customer-facing work from day one, shipping products, speaking directly with customers and iterating quickly. The Global Public Sector team builds custom AI applications, training data pipelines for national LLMs, evaluation infrastructure, agentic AI tooling and fraud-detection systems, working in Python, TypeScript, React and MongoDB.
Multiverse London
Coordinates onboarding and ongoing training for coaches and instructors, handling scheduling, materials, certification tracking and compliance. Owns enablement projects end to end, manages the shared Senior Coach and Instructor pool day to day, and keeps the content library and reporting for MBRs and QBRs in order.
Multiverse London
Owns the end-to-end journey for a portfolio of Enterprise accounts, from sales handover through launch, adoption and renewal. Builds 12-month mutual action plans, runs executive business reviews and correlates learner data with client KPIs to prove ROI and drive expansion. Acts as the internal voice of the customer, aligning delivery, product and support teams.
Reperio Human Capital Dublin, Ireland £388 – £474 pd
Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.
University of Exeter Exeter £21,805 pa
Develops explainable, trustworthy machine-learning models for early dementia detection, integrating multimodal data such as neuroimaging, cognitive assessments, genetics and biomarkers. Uses latent knowledge-enhanced representations, vision-language agentic frameworks and uncertainty quantification, with clinician evaluation of bias and fairness. Validated through a longitudinal multimodal prediction and explanation system.
Quantum Group London £42,000 – £45,000 pa
Analyse aged-receivables, debtor and payment data to identify credit and counterparty risk, estimate expected losses, and assess liquidity and cash-flow exposures. Build Python statistical models for default prediction, run stress tests, and develop Power BI dashboards tracking debtor days and collection rates. Maintain the risk register, prepare monthly leadership reports, and support audit and compliance work.
Adria Solutions Huddersfield £55,000 – £70,000 pa
Develops software and applied AI models for machine vision, working across C++, C# and Python to build image-processing algorithms and integrate models into reliable applications. Involves dataset preparation, model evaluation, performance tuning for accuracy and inference speed, automated testing and debugging of vision pipelines. Hybrid or remote, with a path to lead an AI team.
NVIDIA Reading
Serve as the first line of technical expertise between NVIDIA, Hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Develop and demonstrate GenAI and accelerated computing solutions, optimise GPU training and inference pipelines, and engage developers, researchers and senior technical leaders.
Tenth Revolution Group London £75,000 – £105,000 pa
Builds and deploys production LLM and Generative AI applications for enterprise clients, including RAG solutions, scalable data pipelines and AI-powered services. Works in a collaborative consultancy team of engineers and architects, applying software engineering best practices to take AI from proof of concept into production, with monitoring and optimisation of live systems.
