Machine Learning Engineer

Cadillac Formula 1 Team
Silverstone
9 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Cadillac Formula 1™ is excited to be on the grid for the 2026 FIA Formula One™ World Championship. Our new team is gearing up for rapid growth. To achieve our goals, we need to create and sustain a high-performance culture in every area. We have ambitious plans to build an outstanding operation that can compete at the highest level. 

From exceptional Engineering and Design talent to a world-class race team, supported by specialists in off-track roles - we are assembling the expertise needed to drive this operation forward and compete at the highest level. 

Being a part of this team, will accelerate your career. Take a closer look at the role: 

Job Description:

We have an exciting opportunity for a Machine Learning Engineer to join the Team at our new Silverstone Facility.  In this role, you will be involved in supporting the development of AI and machine learning techniques to enhance capabilities and effectiveness.

 

What you will be doing:

·       Innovate in leveraging state-of-the-art machine learning techniques to deliver capability requirements.

·       Design and build data pipelines utilising AI/ML to enhance the efficiency and effectiveness of our operations.

·       Identify the best libraries and frameworks for the application of machine learning techniques pertinent to the technical applications.

·       Apply technical capabilities across workstreams spanning machine learning, data science, and numerical simulation.

·       Collaborate with other teams to develop, train and validate models.

·       Investigate and research the latest machine learning technologies and techniques, presenting and sharing knowledge between team members.

Requirements

·       A degree in a relevant discipline, such as engineering, physics, computer science, mathematics, or similar.

·       A minimum of 2 years relevant experience in a similar role, ideally in the motorsport  industry.

·       A strong background in statistics, data science, machine learning algorithms, and optimisation techniques.

·       Experience in building machine learning models with PyTorch or equivalent, and using tools such as PyVista and NumPy.

·       Practical experience with software development methods and best practices, such as using version control software.

·       Enthusiasm for the application of machine learning methods to solve engineering problems.

·       Communicate effectively with key stakeholders/directors.

·       Clear and concise communication, verbally and with the use of email.

·       Strong levels of IT skills including MS Office, Word, Excel, and PowerPoint.

·       Positively contribute to an open and inclusive culture.

Please note that additional security checks may be required as part of the recruitment process. This may include a background check covering a minimum of the past five years and a criminal record check. 

This job description reflects the major tasks to be carried out by the postholder and identifies the level of responsibility at which the postholder will be required to work. Subject to the discretion of the Company, the postholder will carry out the duties specified above together with such other duties or tasks for the Company as reasonably required. You may also be required to perform additional duties for the Company from time to time commensurate with your skills and experience. 

Please be aware that we will be reviewing applicants on a rolling basis and this job posting will close once a suitable candidate is identified. We encourage all interested individuals to submit their application as soon as possible.  As an equal opportunities employer, we are committed to the equal treatment of all current and prospective employees and does not condone discrimination on the basis of age, disability, sex, sexual orientation, pregnancy or maternity, race or ethnicity, religion or belief, gender identity or marriage and civil partnership. We aspire to have a diverse and inclusive workplace and strongly encourage suitably qualified applicants from a wide range of backgrounds to apply.

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.