About the Company Williams Grand Prix Technologies help solve our customers’ engineering challenges using world-leading capabilities in the areas of platform dynamics, advanced materials, simulation, testing, high performance computing, data analytics, artificial intelligence and machine learning.
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Operating across a wide spectrum of sectors, from aerospace and premium automotive to sport and lifestyle, we deliver a unique and world-class offering that draws on an unrivalled and trusted pedigree, earned at the forefront of motorsport engineering and diversified advanced engineering excellence.
Our team operates from our headquarters in Grove, UK.
By combining exceptional talent with unique engineering assets, we tackle our clients’ most complex challenges with the agility and precision that our motorsport heritage demands.
Position Overview We are seeking an experienced and innovative Senior Control Systems Engineer to lead the development and optimisation of advanced control systems.
This role requires implementing cutting-edge technologies into the development process, including model-based development (MBD), automated verification and validation (V&V), and the integration of machine learning algorithms to enhance system performance.
As a senior engineer, you will take a leading role in the design, simulation, and deployment of control strategies across high-performance applications, working closely with multi-disciplinary teams.
The ideal candidate will bring strong expertise in control system development, leadership experience in managing complex projects, and a passion for integrating advanced technologies like machine learning into control systems.
Key Responsibilities Lead the development, implementation, and optimization of control systems using model-based development (MBD) methodologies to improve precision, adaptability, and performance.
Integrate machine learning algorithms into control systems to enhance system efficiency, adaptability, and real-time decision-making capabilities.
Lead the implementation and continuous improvement of automated verification and validation (V&V) processes to ensure system robustness, reliability, and safety.
Collaborate with multi-disciplinary teams, including mechanical, electrical, and data science engineers, to design control algorithms that enhance vehicle dynamics, performance, and safety.
Utilize MATLAB/Simulink and other tools to model, simulate, validate, and deploy control algorithms across various systems.
Mentor and guide junior engineers on best practices in control systems development, verification, and testing methodologies.
Lead real-time control system calibration and tuning processes, optimizing performance across varying operating conditions.
Drive innovation by implementing hardware-in-the-loop (HIL) simulations, ensuring high-fidelity testing and system-level validation.
Ensure control systems meet relevant functional safety standards and industry regulations, including ISO 26262 compliance.
Stay current with advancements in machine learning, control theory, and system automation, applying these innovations to drive continuous improvement in system performance.
Preferred Candidate Profile: Bachelor’s or Master’s Degree in Control Systems Engineering, Electrical Engineering, Mechatronics, or a related field; PhD preferred.
7 years of experience in control systems development, including model-based design, automated verification, and algorithm integration.
Expertise in MATLAB/Simulink and other relevant modelling and simulation tools for control systems development and validation.
Strong understanding of machine learning techniques and their application in control system optimization and real-time decision-making.
Proven experience with automated verification and validation (V&V) processes, including HIL simulations and system-level testing.
Demonstrated ability to implement control systems in real-time embedded environments, ensuring optimal system performance and reliability.
Experience working in high-performance industries such as motorsports, automotive, aerospace, or other dynamic environments.
Strong leadership and project management skills, with a track record of leading complex control system development projects to successful completion.
Excellent problem-solving abilities, with a focus on driving innovation and optimizing control systems for high-performance applications.
Desirable Knowledge & Experience: Hands-on experience with machine learning algorithms for control systems, including adaptive and predictive control strategies.
Familiarity with functional safety standards (e.g., ISO 26262) and ensuring control systems meet compliance and safety requirements.
Knowledge of digital twin technology for real-time system monitoring, predictive maintenance, and performance optimization.
Experience with control system calibration and tuning tools and methodologies for real-time performance optimization.
Why Join Us? Williams Grand Prix Technologies is based at the Williams Racing Campus in a multi acre complex located in Grove, Oxfordshire.
The Williams Group offer a competitive holiday package, staff events/open days, a subsidised restaurant on site and various car schemes.
We have an on-site gym (open 24 hours a day) as well as various fitness classes including outdoors bootcamps, pilates and yoga free for all staff and contractors to use.
Aside from these benefits we can offer free onsite parking and large open green spaces to unwind during breaks.
We are a based just 30 mins from Oxford City Centre by bus.
At Williams Grand Prix Technologies, you will be part of a pioneering team at the forefront of engineering innovation.
You'll have the opportunity to work on exciting projects across various industries, making a global impact.
We offer a collaborative and dynamic work environment where your skills and creativity will be valued and encouraged.
Williams is an equal opportunity employer that values diversity and inclusion.
We are happy to discuss reasonable job adjustments.
Please note: due to the high levels of interest we're experiencing, all agency enquires should use the careers email address found on our website careers page.
Thank you.