At a Glance
- Tasks: Leverage machine learning for design optimisation and performance analysis in Formula 1 power units.
- Company: Join GM Performance Power Units, a leader in automotive innovation.
- Benefits: Competitive salary, hands-on experience, and a chance to work in F1 engineering.
- Other info: Dynamic team culture focused on precision and innovation.
- Why this job: Be at the forefront of F1 technology and make a real impact on performance.
- Qualifications: Bachelor's in relevant fields; experience with neural networks and optimisation required.
The predicted salary is between 60000 - 80000 £ per year.
GM Performance Power Units (GM PPU) seeks an ERS ML Design Optimization Engineer to join our team in Concord, NC. This role leverages ML for design optimization, simulation acceleration, and performance analysis of ERS systems (MGU-K, CU-K, ES) using telemetry and physics-based data. Focus on surrogate models to reduce sim cycles while meeting FIA constraints.
Key Responsibilities:
- Build neural network surrogates (e.g., PINNs, graph nets) emulating ERS physics across thermal, electrical, degradation behaviours.
- Implement tool-agnostic GA/BO optimization loops for multi-objective ERS design (mass/power/reliability).
- Fuse/process petabyte-scale datasets from bench/dyno/track + DiL/HiL/SiL sims for training/validation.
- Conduct sensitivity analysis, uncertainty quantification on ERS parameter spaces.
- Develop ML-accelerated workflows integrated with NX/AVL/MATLAB/ANSYS sim chains.
- Validate models against real duty cycles; iterate for FIA-constrained optima.
- Document optimization pipelines, neural architectures, and results for design reviews.
Required Qualifications:
- Bachelor's in CS/EE/Math/Physics; Master's/PhD in ML/scientific computing preferred.
- 3+ years building neural surrogates for engineering sims; GA/BO optimization experience.
- Expert in PyTorch/TensorFlow/JAX; large-scale time-series/physics data pipelines.
- Proficiency handling multi-fidelity datasets (real + DiL/HiL/SiL).
- Familiarity with hybrid powertrains, multi-physics sim tools.
Desirable Skills:
- F1 ERS plant modeling (cell/MGU/ES performance prediction).
- Neural operators/PINNs for PDE surrogates; multi-fidelity BO.
- HPC workflows, data versioning (DVC), containerization.
- Domain expertise in e-motors, batteries, power electronics.
Personal Attributes:
- Delivers under aggressive development timelines.
- Innovates across model/design/compute trade-offs.
- Communicates complex ML insights to design engineers.
- Rigorous validator of sim fidelity against reality.
- Passionate about F1 performance engineering.
Why Join Us
You’ll play a pivotal role in ensuring the reliability and performance of a next-generation Formula 1 power unit. Our culture rewards precision, innovation, and the relentless pursuit of performance.
Please note: GM Performance Power Units and all affiliated companies are Equal Opportunity employer(s). Minorities, women, veterans, and individuals with disabilities are encouraged to apply.
Formula 1 ERS ML Design Optimization Engineer in Concord employer: GM Performance Power Units
At GM Performance Power Units in Concord, NC, we offer an exceptional work environment that fosters innovation and precision in the high-stakes world of Formula 1 engineering. Our culture prioritises employee growth through hands-on experience with cutting-edge machine learning technologies and collaborative projects, ensuring that every team member contributes to the relentless pursuit of performance excellence. Join us to be part of a diverse team where your expertise will directly impact the future of motorsport technology.
Contact Details:
GM Performance Power Units Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Formula 1 ERS ML Design Optimization Engineer in Concord
✨Tip Number 1
Network like a pro! Reach out to folks in the F1 and engineering circles on LinkedIn or at industry events. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML and simulation. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with neural networks and optimization loops, as these are key for the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Formula 1 ERS ML Design Optimization Engineer in Concord
Some tips for your application 🫡
Show Your Passion for F1:Let us know why you're excited about working in Formula 1! Share your enthusiasm for performance engineering and how it drives you to innovate. A personal touch can really make your application stand out.
Tailor Your CV and Cover Letter:Make sure your CV and cover letter are tailored to the role of ERS ML Design Optimization Engineer. Highlight your experience with neural networks, optimization loops, and any relevant projects that showcase your skills in ML and engineering.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain your qualifications and experiences. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, it shows you’re serious about joining our team at GM Performance Power Units.
How to prepare for a job interview at GM Performance Power Units
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially around neural networks and surrogate models. Be ready to discuss your experience with PyTorch or TensorFlow, as well as any specific projects where you've built neural surrogates for engineering simulations.
✨Understand the F1 Context
Familiarise yourself with Formula 1 power units and the specific challenges they face. Knowing about hybrid powertrains and how ERS systems work will show your passion and understanding of the industry, which is crucial for this role.
✨Prepare for Technical Questions
Expect technical questions related to optimisation loops and data processing. Think about how you would approach multi-objective design problems and be prepared to explain your thought process clearly. Practice articulating complex ideas simply, as you'll need to communicate these insights to design engineers.
✨Show Your Passion
Let your enthusiasm for F1 performance engineering shine through. Share any personal projects or experiences that demonstrate your commitment to innovation and precision in engineering. This role is all about pushing boundaries, so showing that you’re driven by performance will set you apart.
