Motorsports F1 Performance Engineer

General Motors
Wantage
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst – Motorsport

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Concord, NC three times per week, at minimum.The RoleThis role will work within the GM Motorsports Program to develop performance metrics, conceptualize new analysis methods, and implement these techniques to produce improved on-track performance. The focus of the Performance Engineer is primarily on the validation, refinement, and application of new tools and methods to develop vehicle setups for specific events and/or derive new directions for future vehicle development.  This team will initially focus on supporting new GM motorsports ventures, including exploratory studies to support the Andretti Cadillac Formula 1 program.  With the focus on new programs, work will include the development and implementation of vehicle, track, and competitor characterizations methods.What You'll DoCollaborate with GM supported teams and GM personnel to understand team objectives, contribute to a coordinated development effort, and convey findings to all necessary groupsContinuously strive to improve GM Motorsports programs’ analysis methods and vehicle dynamics understanding by:Reimagining new and better solutions to common problems or questionsPrototyping new ideas and validating these against track and test dataWorking with GM Software team to implement solutions in our production toolsImplement vehicle simulation, data analysis methods, and other tools to develop race winning solutions through:Race-specific setup refinementConceptual studies to guide big-picture development effortsCompetitor analysis and event characterizationClearly present findings, recommendations, and analysis results through well organized and actionable reports and in-person follow-up#LI-LP2Additional Job Description Your Skills & Abilities (Required Qualifications)Bachelor’s Degree in Engineering, Physics, or related subject5+ years of experience in a top-level motorsports series including NASCAR, IMSA, F1, IndyCar, WEC, or similar3+ years of experience in F1Intimate knowledge of simulation workflows in a professional motorsports organization including both offline simulation and the DIL simulator.  Experience using simulation tools to optimize vehicle performanceProficient programing in python, MATLAB, or similar languageExtensive experience analyzing on-track performance through both application vehicle dynamics principles and statistical methodsStrong organization skills, forward thinking mentality, and a superb attention to detailAbility to multi-task in a dynamic, constantly evolving environment, with exceptional work ethic and integrityThis job may be eligible for relocation benefitsWhat Will Give You a Competitive Edge (Preferred Qualifications)Master’s Degree in Engineering, Physics, or related subjectRace Engineering experience in a F1 program with intimate knowledge of race car setup, event preparation, technical inspection, race procedures and race strategyProficiency in Motorsports data analysis software including Pi Toolbox, Atlas, Motec or similarKnowledge and experience in tire modeling, construction, testing, and validationExperience with aerodynamic testing and applying physical and/or CFD results to vehicle modeling tools for on-track performance optimizationFamiliarity with vehicle testing methods and data reduction from on-track testing, SPMM, and 7-postAbout GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.Why Join Us  We aspire to be the most inclusive company in the world. We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Our Work Appropriately philosophy supports our foundation of inclusion and provides employees the flexibility to work where they can have the greatest impact on achieving our goals, dependent on role needs. Every day, we want every employee, no matter their background, ethnicity, preferences, or location, to feel they belong to one General Motors team.Benefits Overview The goal of the General Motors total rewards program is to support the health and well-being of you and your family. Our comprehensive compensation plan incudes, the following benefits, in addition to many others:Considering making an application for this job Check all the details in this job description, and then click on Apply.• Paid time off including vacation days, holidays, and parental leave for mothers, fathers and adoptive parents;• Healthcare (including a triple tax advantaged health savings account and wellness incentive), dental, vision and life insurance plans to cover you and your family;• Company and matching contributions to 401K savings plan to help you save for retirement;• Global recognition program for peers and leaders to recognize and be recognized for results and behaviors that reflect our company values;• Tuition assistance and student loan refinancing;• Discount on GM vehicles for you, your family and friends.Diversity Information General Motors is committed to being a workplace that is not only free of discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that workforce diversity creates an environment in which our employees can thrive and develop better products for our customers.   We understand and embrace the variety through which people gain experiences whether through professional, personal, educational, or volunteer opportunities. GM is proud to be an equal opportunity employer.We encourage interested candidates to review the key responsibilities and qualifications and apply for any positions that match your skills and capabilities.Equal Employment Opportunity Statements GM is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. GM is committed to providing a work environment free from unlawful discrimination and advancing equal employment opportunities for all qualified individuals. As part of this commitment, all practices and decisions relating to terms and conditions of employment, including, but not limited to, recruiting, hiring, training, promotion, discipline, compensation, benefits, and termination of employment are made without regard to an individual's protected characteristics. For purposes of this policy, “protected characteristics" include an individual's actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, weight, height, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state or local laws and ordinances.  If you need a reasonable accommodation to assist with your job search or application for employment, email us at  or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.​

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.