Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Adoption Manager

Wellington
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - Machine Learning and AI

AI and Machine Learning Trends 2025: A UK Hiring Outlook

Senior Machine Learning Engineer

ML (Machine Learning) Engineer

Engineering Program Manager, Machine Learning

AI Infrastructure and Data Engineering Site Leader (Edinburgh)

About the Role

We are seeking an experienced and innovative AI & Innovation Specialist to join our client. In this role, you will be responsible for identifying, exploring, and implementing AI-driven solutions that can enhance our business operations. As a key member of our team, you will bridge the gap between technical capabilities and business impact, driving the adoption of AI technologies to support our growth and success.

Key Responsibilities:

Identify AI opportunities: Conduct research and evaluate potential AI use cases that can drive efficiency, automation, or competitive advantage.
Collaborate across teams: Work closely with production, R&D, and commercial teams to understand business needs and how AI can enhance processes.
AI Implementation Support: Assist in developing and testing AI-driven solutions, working alongside external AI consultants and internal teams.
Data & Insights: Support data analysis efforts to assess trends, performance, and AI model effectiveness.
AI Training & Awareness: Help upskill internal teams by explaining AI concepts and ensuring effective adoption of new tools.
Monitor AI Trends: Stay informed on the latest AI developments and assess how they could be applied within the business.

What We're Looking For:

Degree in Computer Science, Data Science, AI, Business Analytics, or a related field.
1-3 years of experience in AI, data science, or technology-driven innovation.
Understanding of AI tools, automation, and machine learning concepts (hands-on coding experience is beneficial but not essential).
Strong problem-solving and analytical skills with a commercial mindset.
Ability to communicate AI concepts to non-technical stakeholders.

Nice to Have:

Experience in manufacturing, production, or supply chain optimisation.
Exposure to working with AI consultancies or external data teams.
Understanding of business process automation

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.