Senior or Principal E-Drive Controls Engineer, Birmingham

TN United Kingdom
Birmingham
1 month ago
Applications closed

Related Jobs

View all jobs

Principal Software Engineer

Senior Machine Learning Engineer

Senior Software Engineer (GO/PHP)

Principal Data Scientist / AI Engineer

Principal MLOps Engineer - Chase UK

Senior Data Analyst

Social network you want to login/join with:

Senior or Principal E-Drive Controls Engineer, Birmingham

Client:

Location:Birmingham, United Kingdom

Job Category:-

EU work permit required:Yes

Job Reference:0af9dddb5ee5

Job Views:100

Posted:22.01.2025

Expiry Date:08.03.2025

Job Description:

Job summary

Do you have a strong background in e-drive and power electronics control systems? If so, you might be the perfect candidate for this exciting opportunity!

Key skills required for this role:

  • E- Drives
  • Control Systems
  • Matlab and Simulink

Important:

  • E-Drive Controls
  • Matlab
  • Simulink

Are you passionate about developing the next generation of electrified, connected, and intelligent powertrains? A leading automotive company is looking for an experienced e-drive and power electronics controls engineer to join their UK R&D Centre and lead their work in this area. You will be part of a dynamic and cross-functional team that is at the forefront of transforming the powertrains of their passenger car business.

Responsibilities:

  • Supporting the development of e-drive and power electronics control systems
  • Capturing and analysing requirements from different stakeholders
  • Designing control algorithms & strategies (using MATLAB/Simulink) and autocode generation of production intent code
  • Designing system diagnostics and CAN communication specifications
  • Development of diagnostic and safety monitoring strategies
  • Developing validation tests for electrical test bench, HiL and vehicle
  • Providing expertise for investigations and problem-solving activities
  • Supporting system and hardware DFMEA and functional safety analysis
  • Managing the technical delivery of suppliers

To be successful in this role, you will need:

  • Bachelor's degree or equivalent in Electrical/Electronic or Control System Engineering
  • Proven experience working with real-time embedded control systems
  • Background in Electrical Drive control software development
  • Experience of developing and testing control algorithms in MATLAB/Simulink
  • Knowledge of power electronics topologies and simulation techniques
  • Knowledge of electrical drive topologies and their drive control
  • Experience with data logging and calibration tools (INCA, CANalyzer, CANape)
  • Experience of using automotive communication protocols: CAN/ CAN FD
  • Experience of using and applying automotive software quality
  • Direct experience is essential with preferably some of this within the Automotive Industry
  • Experience of applying system engineering methods
  • Strong numeracy and literacy skills, including the ability to write clear documentation
  • Excellent communication skills and able to work as part of a cross functional team
  • A working knowledge of Functional Safety Standard ISO26262 would be an advantage
  • Experience of working with hybrid and battery electric vehicles would be an advantage
  • Experience of undertaking DFMEA at System and Sub-System level, with good logical reasoning
  • Organised and able to prioritise effectively
  • Eligibility to work in the UK

This role is fully on site.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.