Head of Artificial Intelligence – Smart Manufacturing

Bristol
9 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Head of Data Compliance

Data Scientist

Junior Ecommerce and Marketplace Data Analyst

Principal Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Data Scientist AI

Head of Artificial Intelligence – Smart Manufacturing

A UK-based manufacturing group, headquartered in Bristol, is undergoing a full-scale digital transformation — placing AI and machine learning at the heart of its operational strategy.

To lead this journey, we are hiring a Head of Artificial Intelligence to define, build, and scale enterprise-grade AI solutions across production, supply chain, and predictive analytics.

This is a senior leadership role with board visibility and direct influence on the strategic roadmap of a business at the forefront of Industry 4.0.

Key Responsibilities



Define and lead the company-wide AI vision and roadmap.

*

Hire and manage a high-performance team of ML Engineers and Data Scientists.

*

Oversee the delivery of AI projects, from pilot to full deployment, across smart factory operations.

*

Translate manufacturing business needs into scalable AI/ML solutions.

*

Represent the AI function in strategic meetings with board members and external stakeholders.

What We're Looking For

*

Proven experience leading AI teams within a manufacturing or industrial setting.

*

Strong hands-on knowledge of machine learning, predictive maintenance, and/or digital twins.

*

Technical proficiency in Python, TensorFlow, PyTorch, or similar frameworks.

*

Excellent communication skills and stakeholder management experience at the senior level.

*

Bristol-based or open to commuting 1–2 days a week to the HQ.

What’s on Offer

*

Highly visible strategic leadership position in a business poised for growth.

*

Influence over multi-million-pound investment decisions in AI and tech.

*

Generous bonus and potential equity package.

*

Flexibility to shape and build a world-class AI function from the ground up.

Apply Now
Submit your CV today to explore this exciting opportunity to lead AI innovation from the ground up in Bristol’s industrial heartland

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.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.