Systems Engineer

Henderson Scott
Cheltenham
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Defence Data Engineer: ETL & Analytics for M&S

Real-Time Computer Vision Engineer - Production Focus

Senior Computer Vision Engineer...

Senior Computer Vision Engineer

Senior Machine Learning Engineer

Systems EngineerWe are currently hiring on behalf of an industry-leading engineering company who have several systems engineering roles at different levels of seniority across the business to support the development and production of their product range. In these roles, you will gain a broad engineering experience, engage with partners, co-ordinate technology specialists, and develop advanced systems engineering techniques.We are looking for candidates who have experience in some/any of the following skill areas:MATLAB/SimulinkSystems Integration and System DesignElectro-Optics/InfraredRF/Microwave systemsSimulation & ModellingAlgorithm DevelopmentRequirements engineeringConcept assessment and design trade studiesSystem architecture design and functional modellingPerformance assessment and systems behaviour analysisVerification, Validation and CertificationModel based engineering techniques e.g. MBSE or SysMLSystems Engineering tools e.g. IBM DOORS Next, RhapsodyWhat we need from you:Experience of systems engineering within a complex, high technology engineering or manufacturing environmentExperience with good systems engineering practicesGood written and verbal communication and presentation skillsGood analytical and problem-solving skillsThe ability to plan and control your workIf you would like to know more details about the position or want to register your interest, hit apply below. We'd love to hear from you!TPBN1_UKTJ

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 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.

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.

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.