Senior Race Testing Operations Engineer - Formula1

McLaren Racing
Woking
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Data Scientist

Data Scientist

Senior Data Engineer

Senior Director Artificial Intelligence/Machine Learning

Principal Data Engineer

At McLaren, our mission is to set the standard for high performance in sport. Everyone, in every part of the team, has a role to play. So if you want to test your ideas with the world watching... And measure your progress in milliseconds... And play your part in racing history... You belong here. High performance starts with you.

Purpose of the Role:

As a Senior Specialist, Software Operations, you will play a crucial role in ensuring the optimal performance and reliability of the software systems that underpin the McLaren Formula 1 Team. This role is responsible for providing operational support, developing monitoring tools such as dashboards and alerts, automation, and performing system administration tasks before, during, and after F1 tests. The successful candidate will work closely with various team members to ensure our systems run smoothly, contributing to the team's overall performance on and off the track.

Role Dimensions:

The Software & Data Science department is responsible for the analysis, design, and delivery of bespoke software tools and methodologies that drive the performance of McLaren in Formula 1. In this role, you will own the software and hardware environment that makes F1 testing possible. This environment supports multi-dimensional simulation and car setup optimisation and supports trackside operational decision-making tools including real-time telemetry analysis, race strategy, and historic recording of every aspect of racing. We are a cross-functional group, bringing together data science, machine learning, software engineering, and DevOps to deliver performance-focused platforms and solutions.

Due to the nature of F1 testing, flexibility to work out of office hours and weekends will be required. For test weeks, you’ll offset your week (Weds-Sun) and be based at the prestigious McLaren Technology Centre. During non-test weeks, a proportion of your time can be spent working from home.

Principal Accountabilities:

Operational Support:

  • Provide first and second-line support for software systems used by the McLaren Formula 1 team during test events.
  • Effectively prioritise issue resolution and support requests originating at track.
  • Troubleshoot and resolve software issues in a timely manner, ensuring that teammates are kept up to date throughout.
  • Collaborate with software engineers and IT staff to address and resolve technical problems.
  • Document incidents, solutions, and standard operating procedures for future reference.

Testing Platforms:

  • Implement and configure our monitoring systems to track key performance indicators (KPIs) and system health metrics used at Test Events.
  • Develop and maintain monitoring dashboards and alert systems to ensure real-time visibility into system performance.
  • Analyse monitoring data to identify trends, potential issues, and areas for improvement.
  • Work with stakeholders to customise monitoring tools to meet specific needs and requirements.

System Administration:

  • Perform routine system administration tasks, including software deployment and configuration.
  • Build automations for operational processes that will make the team more efficient.
  • Manage user accounts, permissions, and access controls.
  • Work closely with DevOps Engineers to maintain the reliable operation of our Kubernetes.

Knowledge, Skills and Experience:

Essential

  • BSc in Computer Science or equivalent discipline (2:1 or above) or equivalent industry experience.
  • Proven experience in software systems support, preferably within a high-performance or fast-paced environment.
  • Proficiency in developing monitoring tools and dashboards using technologies such as Grafana, Prometheus, or similar.
  • Strong understanding of system administration, including Windows and Linux operating systems.
  • Familiarity with containerisation technologies e.g., Docker and Kubernetes.
  • Strong experience with scripting languages (e.g., Python, Bash) for automation and tool development.
  • Excellent problem-solving skills and the ability to work under pressure.
  • Familiarity with a programming language such as C#, Python, or TypeScript/JavaScript.
  • Familiarity with relational (SQL Server, MySQL, Postgres) and/or NoSQL (MongoDB) databases.

Desirable

  • Ability to use large unfamiliar codebases to help diagnose issues.
  • Knowledge of network protocols, storage systems, and troubleshooting techniques.

Personal Attributes:

  • Strong attention to detail and a proactive approach to identifying, owning, and resolving issues.
  • Excellent communication skills, both verbal and written, to effectively interact with team members and stakeholders.
  • Ability to work independently as well as part of a collaborative team environment.
  • High level of motivation, with a passion for motorsports and a commitment to excellence.
  • Flexibility to adapt to the dynamic and fast-paced nature of the Formula 1 industry.
  • Strong organisational skills and the ability to manage multiple tasks and priorities simultaneously.
  • Approachable, with balanced judgment and a high level of personal integrity.
  • Reliable and punctual – willing to put the team first.
  • Willingness to work non-standard hours, including weekends and travel, as required by the racing calendar.

What can McLaren offer?

We constantly strive to be better tomorrow than we are today. Our ambition is to be the most pioneering and exhilarating racing team in the world, and our collective task is to set the standards for high performance in sport. We show up every day with energy and enthusiasm, ready to play our part.

We encourage and support diversity, equity and inclusion. We will actively promote a culture that values difference and eliminates discrimination in our workplace.

McLaren Racing is based at the iconic McLaren Technology Centre (MTC) near Woking. Here at McLaren, we offer hybrid working with 3 days a week based in the MTC.

Our state-of-the-art, sustainable campus offers many facilities including a gym, restaurant and indoor and outdoor break-out areas, as well as direct access to park and common land. The MTC is connected to Woking mainline station via regular shuttle buses, from which London Waterloo is a 30 minute train ride.

We offer a comprehensive package of benefits including private healthcare, car schemes, life insurance and generous pension contributions.

#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.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Jobs

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.