National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

▷ 3 Days Left: CAE Process Automation Engineer

Quintessential Design Services Limited
Coventry
7 months ago
Applications closed

Job description About Us: QDSL (Quintessential DesignServices Limited) is an engineering and technology consultancybased in the UK, supporting client projects in field of EngineeringInnovations, Research & Development and IT. We offerengineering support in Automotive, Aerospace, Energy and IT. Due tothe increasing demand of Engineering projects, QDSL is looking togrow the recruitment team. This is a great opportunity to join afast-growing team with strong core values on Quality of Health,Work / Work-Life Balance, accountability, service and Integrity.Position: CAE Process Automation - Project Engineer Job ID:QDSL082301 Job Type: Permanent Location: Warwickshire KeyResponsibilities - Responsible for automating virtual CAEtechniques for battery, fuel cell, electric drive unit and ICengine durability. Powertrain CAE requires robust and repeatableprocesses to support the digital product development phase. Theapplication of such tools is used to assess and optimise designsolutions as well as validating the design prior to the hardwarerelease. - Develop tools and techniques which enhance speed,capability, improve quality and robustness of virtual models. -Develop tools and techniques which enhance speed, capability,improve quality and robustness of virtual models - Develop codingto automate new and existing CAE process to reduce time and improvequality. - Determine automation and optimisation requirements,metrics and targets. - Identify process short comings andopportunities to improve. - Support department prevent reoccurrenceprocess identify CAE failures and undertaking annual projects toresolve. - Support methods reviews as appropriate contributingideas. - Support agile ceremonies such as start-up, backlogrefinement, retrospective and sprint planning. - Presentachievements at showcases. - Support internal customers of ourbusiness where necessary. - Support software vendors, universitiesand engineering service providers when necessary. - Supportoutsourced methods projects as required. - Support the training ofCAE members. - Support familiarisation of CAE members with CAEautomation processes. - Support the design, development workstreamswithin the scope of the engineering development projects. - Conductthe analysis / simulations and development with utmost qualitywithin agile framework. - Dynamic & static attribute targets tobe integrated into the product design assessment. Support prototypedesign freeze activities for customer applications, supportcustomer production / prototype sites & liaise with theirengineering team. - Develop and deliver new process trainingmaterial. - Undertake any other work as directed by their linemanager in connection with their job as may be requested. - Supportissue resolution and warranty activity as required. - Undertakevirtual verification of the PT units as required. Skills Knowledgeand Experience Essential: - Good understanding of processautomation and optimisation, including pre-processing andpost-processing automation. - Working knowledge and experience ofCAE methodologies. - Previous experience and background in solvingcomplex technical ideas and challenges. - Previous experience ofdelivering engineering or analytical projects. - Competent in theuse of the following software and associated pre and postprocessing packages: VBA / MATLAB / Simulink / Python / JAVA. -Experience using similar software packages will be considered. -Relevant degree or equivalent experience preferred. Desirable: -Previous experience in any of the following CAE software: - FEA: DSAbaqus. LS Dyna - CFD: Star CCM+, GT Power - Meshing: PreHypermesh,Simlab - Previous experience of battery / electric drive units andinternal combustion component / system level development using CAEto meet defined performance targets. - Experience in continuousimprovements to business processes to support customer service andfinancial objectives. - Experience in advanced physical measurementtechniques. - Experience in proposing product modifications toimprove design. Experience working in AGILE. What we offer (ForPermanent) - Competitive Salary in line with level of experience. -Healthy working environment with no strict KPI’s. - Opportunity tobe part of world class product development projects. - 28 DaysHolidays (Annual + Bank Holidays) and above additional benefits.How to Apply If you are passionate about working on the world-classinnovation projects and meet the requirements of the role, pleaseemail your application to

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.