Software Controls Engineer - F1 / Motorsport

Arden White Limited
10 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer, Prime Video Content Analytics & Products...

Principal Configuration and Data Engineer

Principal Configuration and Data Engineer

Principal Configuration and Data Engineer

Principal Configuration and Data Engineer

Principal Configuration and Data Engineer

Software Controls Engineer - Northampton
F1 / Motorsport

Initial 12-month contract
Hybrid


The Software Controls Engineer role in Calibration and Controls is responsible for identifying, specifying, developing, testing, calibrating, and reviewing ideas that will lead to either performance or reliability improvement on the Power Unit.

A performance improvement could:

  • Be any feature that results in a powertrain performance gain such as fuel consumption, electrical energy usage, heat rejection, drivability.
  • Involve working in close cooperation with Performance Engineering to develop a system.
  • Be any feature that allows operational "ease of use".
  • The Software Controls Engineer is also responsible for developing and maintaining our SiL, HiL, and Test systems, to ensure robust and reliable operation of the powertrain systems on rigs, dynos, or in the vehicle.


THEREFORE WE NEED YOU TO
Be skilled at:

  • Delivering solutions of the highest standard on fast-paced and technically challenging projects.


Have experience of:

  • Model-based software development using Simulink and Stateflow, preferably within an Automotive environment.
  • Specifying, developing, and testing optimal internal combustion engine and hybrid powertrain control systems.
  • Performing validation tests on various platforms (HiL, Rig, Dyno, etc.).
  • Documenting and developing specifications and procedures.


Demonstrate knowledge of:

  • The full software lifecycle including requirements, design, code, and test.
  • Internal combustion engine and hybrid powertrain operation and control.
  • Sensors and actuators used within the powertrain.
  • Powertrain failure modes and their containment.
  • Use of calibration, diagnostic, and measurement tools such as CANape, CANalyzer, WinDarab, and RaceCon.
  • Software applications and processes for delivering high-quality software.
  • Automotive communication protocols (e.g., CAN, Ethernet).


Hold these qualifications:
Essential:

  • BEng/BSc qualified (2:1 minimum) in Degree level or higher in software or engineering-related discipline.
  • Software design and development experience using one or more of the following tools/languages: MATLAB/Simulink, C/C+.


Desirable:

  • 3+ years post-graduate experience in a challenging and relevant engineering environment.
  • Chartered Engineer Professional Registration.


Be:

  • Highly self-motivated, proactive, and have good organization skills.
  • Creative, innovative, and inquisitive.
  • Detail-oriented and driven to deliver engineering of the highest quality.
  • Able to work to strict deadlines.
  • Excellent problem-solving skills.
  • Good verbal and written communication skills.
  • A team player, promoting a diverse culture of collaboration.
  • Pragmatic, accountable, and credible.
  • Flexible in approach toward working hours.


Success in this role will be if you (Deliverables):

  • Develop Software Control Systems for power unit functions.
  • Manage calibrations for Power unit electronic systems.
  • Specify, develop, and oversee control system tests.
  • Support and champion software development best practices.
  • Provide rapid root cause failure analysis solutions to the business.


Applications:
Please apply with an updated CV and details of current rate/salary and notice period. If you are shortlisted, you will be contacted prior to submission. However, please contact Michael Sorfleet by email if you have any questions.

Please note, these positions CANNOT support sponsorship.

If this role is not for you, but you know someone who may be interested, please forward this email to them. We offer a referral scheme.
Arden White is an equal opportunities employer. If you have any specific requirements or require assistance or reasonable adjustments to be made for you during the selection process due to disability or long-term health condition, we will do our best to assist you.

#J-18808-Ljbffr

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 to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.