ADAS Project Engineer

Jonathan Lee Recruitment Ltd
Wharley End
1 year ago
Applications closed

ADAS Project Engineer - 0968 - £27.94/hr PAYE rateEmbark on a thrilling journey with a leading figure in the automotive industry, renowned for its commitment to innovation, quality, and excellence. This role as an ADAS Project Engineer offers an unparalleled opportunity to contribute to cutting-edge projects that shape the future of mobility. Situated in the vibrant heart of Cranfield, this position promises not only professional growth but also the chance to be part of a dynamic team dedicated to advancing automotive technology.What You Will Do:- Support and lead ADAS development project management, including preparation of material for and hosting key development milestone ADAS step reviews.- Manage the schedule of development and test through to delivery for all ADAS components, including cost and application management.- Spearhead ADAS component cost reduction activities, generating cost reduction ideas and managing their implementation.- Conduct quality up activities for ADAS, identifying key areas for improvement and proposing solutions.- Create and manage development management documentation, including schedules, results, and review presentations for design and cost.- Travel abroad or within the UK for project-related work, occasionally for extended periods.What You Will Bring:- A degree (or equivalent) in a relevant discipline, showcasing your foundation in automotive systems.- Experience with software application into vehicle ECUs in a manufacturing environment, including flashing, coding/configuration, and calibration.- Proficiency in tools like CANalyzer, CAPL, CANoe, CANape, Matlab, or similar for data capture and analysis.- Excellent problem-solving skills, with experience in automotive electronic system development.- Strong communication skills, both written and verbal, with the ability to manage multiple projects simultaneously.This role is a cornerstone in driving the company's vision of integrating cutting-edge design and development practices for vehicles manufactured in European plants. By joining this team, you contribute to a culture of excellence that pushes the boundaries of automotive innovation.Location: The role is based in Cranfield, a hub for automotive excellence and innovation.Interested?:If you're ready to accelerate your career and make a significant impact in the automotive industry, this ADAS Project Engineer role is your next milestone. Apply now to be part of a team that's driving the future of mobility. Don't miss this chance to turn your passion for automotive technology into a rewarding career. Apply today!7This role is Inside IR35.Your CV will be forwarded to Jonathan Lee Recruitment, a leading engineering and manufacturing recruitment consultancy established in 1978. The services advertised by Jonathan Lee Recruitment are those of an Employment Agency.In order for your CV to be processed effectively, please ensure your name, email address, phone number and location (post code OR town OR county, as a minimum) are included

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.