Performance Engineer
Modis
Oxford, United Kingdom
3 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
Oxford, United Kingdom
Tech stack
Data analysis
Design Studio
Machine Learning
Performance Tuning
Simulation Software
Job description
You will collaborate with a multidisciplinary team of engineers across vehicle dynamics, aerodynamics, powertrain and chassis design with a primary focus on the development and optimization of Ford's LMDh entry. In this role, you will be a key contributor to Ford's return to the pinnacle of global endurance racing, ensuring the vehicle is competitive on the world's most demanding stages, including the FIA World Endurance Championship (WEC).
Responsibilities
Process & Integration
- Support the development and implementation of advanced methodologies and processes specifically designed to enhance LMDh performance;
- Collaborate with multiple engineering disciplines to align technical goals with the overall vision of the Performance Engineering Group and the LMDh program;
- Support the design, testing, and optimization of vehicles across concurrent programs, ensuring LMDh milestones are delivered on time and exceed performance expectations;
- Contribute to the continuous improvement of processes to achieve industry-leading performance across all Ford Racing Motorsports disciplines, including NASCAR, Sports Car, NHRA, and Off-Road.
Innovation & Technical Expertise
- Lead the planning and execution of track, lab, and high-fidelity simulator testing to refine the LMDh platform;
- Drive race performance through precision setup changes and the development of sophisticated race strategies tailored for endurance competition;
- Analyze test and race data from all technical disciplines (aerodynamics, vehicle dynamics, and powertrain) to provide actionable recommendations for performance gains;
- Drive innovation by identifying and solving complex vehicle behavior issues with realistic, logical, and implementable technical solutions;
- Leverage expertise in data analysis and emerging technologies to identify new areas of focus for LMDh performance optimization.
Communication & Collaboration
- Provide data-backed recommendations using deep knowledge of racing performance to optimize vehicle systems and resolve technical hurdles;
- Act as a bridge between the Aerodynamics, Vehicle Dynamics, and Powertrain groups to ensure all concepts are integrated optimally for total vehicle performance;
- Foster strong relationships with the design studio, program teams, and internal Ford technical groups to ensure seamless integration across all tools and platforms;
- Collaborate with internal Ford technical teams to improve methodologies, processes, and results, ensuring the LMDh program benefits from the full breadth of Ford's global technical resources.
Requirements
- 5+ years of related experience in the Race Engineering, Motorsports Performance or a related field, with a specific focus on vehicle dynamics, aerodynamics and associated testing methods;
- Bachelor's degree or higher in Engineering or a related subject;
- International and Domestic travel will be required, including weekends., * LMDh or Sportscar experience;
- Extensive experience using data acquisition tools such as Bosch WinDarab, Motec i2, Atlas, Pi Cosworth, etc.;
- Significant experience using simulation software such as Dymola, VI Grade, CarSim, Canopy, etc.;
- Excellent communication and organization skills with ability to prioritize effectively;
- Strong ability and desire to work collaboratively with multiple groups and personnel across numerous disciplines;
- Excellent problem-solving and analytical skills;
- Passion for motorsports and a commitment to excellence;
- Race engineering experience in NASCAR, Indy Car, IMSA, WEC;
- Proven track record of successful project management, including experience managing complex projects with cross-functional teams;
- Prior experience leading and working within a fast-paced, collaborative environment;
- Deep understanding of mechanical design, manufacturing processes, and data analysis techniques;
- Strong knowledge of Machine Learning (ML) and Artificial Intelligence (AI) principles and applications.