Director of Machine Learning

ic resources
remote, uk
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Data Analyst

DATA ENGINEER (MICROSOFT AZURE & FABRIC)

Education-Focused Lecturer, Health Data Science (0.5 FTE)

Machine Learning Engineer

Data Engineers & Scientists -SC required

Director of Machine Learning

IC Resources is delighted to be partnering with an AI-chip manufacturer in their search for a new Director of ML (Machine Learning). Technical expertise and knowledge around developing novel model architectures and training methods for deep-learning hardware accelerators and applications is required to be successful in this role, but on a day-to-day you will be applying your vision and strategy to the technical roadmap and guiding the ML group in the right direction, to the next latest thing in ML.

Do you understand the inner workings of a neural network, as well having the know-how to implement on an AI accelerator? Have you spent at least 2 years building your leadership skills in a lead / head of / director level position? If yes to both and looking for your next step, get in touch.

Essential experience

Good academic background most likely demonstrated by a PhD with relevant publications Understanding in both the theory and application of ML Solid grasp of all the recent developments in ML 5+ years industry and/or extensive post-doc academic research – either must be in the field of ML applied to AI hardware 2+ years of leadership experience

What’s on offer?
Top end salaries for the European market Hybrid across multiple offices, or fully remote is an option if based in UK or mainland EU  
Interested?  This is a great opportunity for a Director of Machine Learning. Please apply now for immediate consideration and speak with Chris Wyatt who is recruiting for this position across the UK and mainland EU.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.