Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Vehicle Tech

Leeds
7 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer, AI Foundations

Senior Data Engineer

Data Engineer

Senior Computer Vision Engineer - UK

Data Engineer

Senior Data Scientist

Vehicle Tech #INDCB

£28,000 - £40,000

Location: Leeds

We are seeking a highly skilled and innovative Vehicle Technology Engineer to join our team. In this role, you will be responsible for the development, integration, and testing of advanced technologies used in vehicles, including autonomous driving systems, electric powertrains, connectivity solutions, and in-vehicle infotainment systems. You will work with a cross-functional team to improve vehicle performance, safety, and user experience while staying ahead of industry trends and regulations.

Key Responsibilities:

Research & Development: Conduct research on emerging vehicle technologies (autonomous systems, electric vehicles, connectivity, etc.), staying updated on industry advancements.
Design & Prototyping: Design and prototype new vehicle technologies, including sensors, communication systems, battery management systems, and control algorithms.
System Integration: Integrate hardware and software components into vehicle systems, ensuring optimal performance, safety, and reliability.
Testing & Validation: Plan and execute testing of new technologies, including simulation, road tests, and software/hardware validation.
Collaboration: Work closely with cross-disciplinary teams, including electrical engineers, software developers, mechanical engineers, and project managers, to ensure project timelines and technical goals are met.
Data Analysis: Analyze vehicle performance data to identify issues, propose solutions, and continuously improve vehicle systems.
Compliance & Standards: Ensure compliance with local and international safety, environmental, and regulatory standards.
Troubleshooting: Identify and resolve issues related to vehicle systems, ensuring minimal downtime and optimal system operation.Required Skills and Qualifications:

Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, Computer Science, Automotive Engineering, or a related field.
Hands-on experience in vehicle system design, integration, and testing.
Proficiency in programming languages such as Python, C++, MATLAB, or other relevant software tools.
Familiarity with vehicle communication protocols (CAN, LIN, Ethernet, etc.) and embedded systems.
Experience with simulation and modeling tools (e.g., Simulink, CarSim, etc.).
Knowledge of electric vehicle powertrains, autonomous driving systems, infotainment, and connected car technologies.
Strong problem-solving, analytical, and troubleshooting skills.
Excellent communication and teamwork abilities.Preferred Skills:

Experience with AI/machine learning techniques applied to autonomous driving or vehicle safety.
Knowledge of automotive cybersecurity principles.
Familiarity with regulatory compliance for autonomous vehicles or electric vehicle infrastructure.
Experience in cloud computing or data analytics for vehicle diagnostics.Work Environment:

This position may require occasional travel for testing, site visits, or industry events

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.