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Featured Jobs

Associate Director, AI & Advanced Analytics

CSL's R&D organization is accelerating innovation to deliver greater impact for patients. With a project-led structure and a focus on collaboration, we’re building a future-ready team that thrives in dynamic biotech ecosystems. Joining CSL now means being part of an agile team committed to developing therapies that make a meaningful difference worldwide. Could you be our next Associate Director,  AI...

CSL
Maidenhead

Senior Technology Specialist - AI

Description Digital Catapult is looking for a Senior Technology Specialist in AI to join our team of experts in applying cutting edge AI to real world challenges. In this pivotal role, you’ll be the technical bridge between complex requirements and high-impact designs, turning visionary concepts into robust digital realities for a diverse range of stakeholders. This initial focus of the...

Digital Catapult
Belfast

Machine Learning Engineer (Forward Deployed)

We’re looking for a Machine Learning Engineer (Forward Deployed) to join a supportive, multidisciplinary team delivering real-world AI/ML systems into operational environments. In this role, you’ll lead software deployments, working closely with users and stakeholders to translate their problems into robust, production-ready machine learning solutions. You’ll rapidly explore, prototype, and deploy ML approaches both within and beyond our core product...

Mind Foundry
Oxford/ Hybrid

Machine Learning Engineer

Your Responsibilities:  Design and deliver scalable AI and machine learning solutions across underwriting, risk, and operations Own the end-to-end ML lifecycle, from feature engineering to deployment and monitoring Build and maintain data pipelines and production workflows using Python, TensorFlow, PyTorch, scikit-learn, AWS (S3, Lambda, SageMaker, Step Functions, Bedrock), Snowflake, and Dataiku Apply MLOps best practices, including CI/CD, automated testing, model...

The Recruitment Company
Waterford

Machine Learning Engineer

Machine Learning Engineer (2–4 Years Experience) London | Hybrid | £50,000 – £60,000 + stock options + Benefits Company Overview We’re an award-winning FinTech building fairer and smarter lending solutions. Our embedded and direct lending products rely on advanced machine learning models trained on billions of financial transactions. As we scale, we are investing in strengthening our core ML capabilities...

SteadyPay
London

Machine Learning Researcher PhD

Machine Learning Researcher (PhD Statistics Python AI R&D) Cambridge / WFH to £85k Make sure to read the full description below, and please apply immediately if you are confident you meet all the requirements. Are you a tech savvy, PhD educated, Machine Learning Researcher looking for an opportunity to work on complex and interesting systems at the cutting edge of...

Client Server
Farnham
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Career Advice

Advance your ML career with expert advice, practical job search tips, and insightful industry guides.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

Education

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.

Careers Jobs

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.

Jobs

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.

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