Jobs at CTM Data & Electrical

Join as an HR Graduate to support HR projects, advise colleagues and managers, improve HR processes and documentation, work on AI-focused internal initiatives, and assist HR change and employee relations activities.

Develop and amplify employer brand through content creation, social channels and events. Curate and publish content on LinkedIn, Glassdoor and careers site, support thought leadership, coordinate employer brand activity at events, manage projects to budget, and measure outcomes to improve recruitment and talent engagement.

Lead architecture and delivery of reusable platform capabilities, driving technical strategy, Spec Driven Development, and AI-assisted tooling adoption. Own end-to-end outcomes across teams, mentor senior engineers, simplify the technical estate, and ensure scalable, secure, observable, high-performance systems.

Lead end-to-end planning, delivery and strategy for internal and external events, managing budgets, suppliers, stakeholder relationships and measurement of event success to support employer brand and company strategy.

10-week placement supporting design, delivery and evaluation of learning programmes. Create digital learning content, maintain learning platforms, produce analytics and insights, support stakeholder engagement, and explore AI-enabled learning innovations while contributing to capability-building projects.

Support L&D Partners to identify learning needs, build stakeholder relationships, analyse skills and performance data, and contribute to digital-first blended learning solutions. Support future-skills initiatives (data, digital, AI), onboarding, mandatory learning, and activities that embed a continuous learning culture. Option to complete a CIPD Level 5 Apprenticeship.

Design, implement, test, secure, and maintain backend services for commercial journeys. Collaborate with product and cross-functional engineering teams, embed testing and security standards, contribute to CI/CD pipelines, and participate in engineering communities and agile delivery practices.

Design, build and maintain scalable automated test frameworks and reusable test solutions. Create API, integration, end-to-end and non-functional tests integrated into CI/CD. Collaborate with engineers, product and architects to embed shift-left testing and quality by design, contribute to tooling, perform root-cause analysis, participate in code reviews and continuously evaluate tools to improve quality engineering practices.

Own end-to-end delivery of production ML and LLM-powered systems: design and build training/deployment pipelines, package and deploy models, implement monitoring for performance and drift, support batch and real-time workloads, evolve internal ML platform and tooling, promote best practices, and provide technical leadership and mentoring across data science and engineering teams.

Lead design and deployment of ML models and pipelines for the AI platform. Translate business problems into measurable ML solutions, design experiments and A/B tests, and own model performance, monitoring, degradation detection and retraining. Champion responsible, explainable AI in a regulated financial context, choose between classical ML, LLMs and agentic approaches, collaborate with ML engineering, product and commercial teams, and mentor junior data scientists.

Perform product and behavioural analysis (funnel, cohort, segmentation), define KPIs, run A/B tests, build dashboards, partner with Product and Analytics Engineering, and apply AI/ML techniques to drive product decisions and experimentation.

Lead design and evolution of the product operating model, implement AI-enabled workflows and tooling, define operational standards across product lifecycle, improve processes and knowledge management, drive adoption of modern product practices, and partner cross-functionally to enable faster, insight-driven product delivery.

Lead technical direction and delivery for Enterprise Services: define strategy and architecture, own end-to-end outcomes, run cross-team initiatives, de-risk complex deliveries, mentor senior engineers, partner with product and ops, manage vendor relationships, and ensure security, compliance, and scalable automation across enterprise platforms.

Design and deliver high-performing email campaigns and templates; own end-to-end email design from concept to build-ready assets; develop and maintain the email design system in Figma; collaborate with CRM, marketing and development for implementation; support A/B testing and optimisation; ensure responsive, accessible, and deliverable designs across email clients and devices.

Lead and grow a team of ML engineers to build and operate production ML and LLM systems—real-time inference APIs, batch data products, and agentic AI—ensuring deployment, monitoring, CI/CD, reproducibility, and measurable business impact.

Support development, execution and optimisation of multi-channel media campaigns (AV, social, digital, OOH). Coordinate with agencies and stakeholders, monitor performance against KPIs, prepare reports/dashboards, manage budgets, implement testing and learning, and recommend optimisations to improve media effectiveness and ROMI.

Lead, coach and grow a high-performing software engineering team. Own technical health, reliability and maintainability of customer-facing systems. Partner on architecture and technical strategy, collaborate with Product to balance delivery and technical debt, champion Agile and AI-augmented engineering practices, and ensure alignment with governance, security and risk requirements.

Provide expert HR advice across the employee lifecycle, manage first-line ER and casework, act as senior escalation point, coach managers, support HRIS testing and system improvements, drive process and service enhancements, and operate autonomously to influence people outcomes.

Lead high‑impact AI and decisioning projects from discovery through production. Define technical roadmaps, design and validate models (including causal/experimentation), partner with engineering to productionise services with monitoring and governance, mentor data scientists, and promote responsible AI practices and platform adoption.

Lead and develop data engineering teams building modern data platforms and large-scale pipelines. Drive technical discussions, improve engineering practices, ensure delivery alignment with product and roadmap, manage incidents, and support hiring, coaching, and cross-functional stakeholder communication to optimise team performance and operational excellence.