AI Control Engineer (Industrial Automation and Mechatronics) in Nottingham

AI Control Engineer (Industrial Automation and Mechatronics) in Nottingham

Nottingham Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Luffy AI

At a Glance

  • Tasks: Join us to develop AI controllers for real-world industrial applications and enhance automation.
  • Company: Luffy AI, a pioneering company in the Physical AI revolution, based in Oxford.
  • Benefits: Competitive salary, bonuses, equity, and hybrid working options.
  • Other info: Unique opportunity to influence a growing startup and work on diverse challenges.
  • Why this job: Be part of a groundbreaking team shaping the future of intelligent machines.
  • Qualifications: Degree in engineering/science and experience with industrial control systems preferred.

The predicted salary is between 60000 - 80000 £ per year.

Luffy AI is the foundation AI company at the forefront of the Physical AI revolution. Every motor, every drive, every system that moves, heats or reacts has run on control algorithms invented before the microchip. A hundred years of industry built on logic that was never designed to learn, never designed to adapt, and never designed to improve. We're changing that. Spun out of the UK Atomic Energy Authority and based at Culham Campus in Oxford, a small office in Bristol, we are a team of engineers, physicists, and AI researchers working on the intelligence that will run the next hundred years - in every factory, every vehicle, every robot, every machine that does something real.

The role involves working on state-of-the-art automation and control, applying novel AI approaches to real-world environments, building AI controllers for industrial customers and their suppliers. This dynamic role is perfect for someone with a broad interest in disciplines such as mechatronics, control engineering, industrial processes, robotics, simulation and modelling, and software engineering. You will be used to working at the interface between software and hardware, unafraid to connect wiring to a controller or to use an oscilloscope, as well as having strong software engineering skills, and enjoy working on challenging, multifaceted problems with real-world applications. Experience of working with mechatronics systems would be a significant advantage.

Your work will contribute to building commercial products and solutions for Luffy AI’s early adopter industrial customers – for example, working to understand and characterise systems such as motors, drones and furnaces to help build better control solutions. As an early team member in a growing startup, you will be in a unique position to influence the direction of the company and tailor the role to your interests.

Your responsibilities:

  • Performing system identification and characterisation of systems, including developing test setups and procedures to empirically improve the validity of digital twin models.
  • Assisting with the development of demo suites and test rigs that help demonstrate the capabilities of our framework to customers.
  • Performing system integration and field testing, including at customer sites.
  • Developing and enhancing control software for real-world applications.
  • Contributing to the development of digital twin models and AI controllers.

Qualifications and experience:

We’d like you to have:

  • University degree in a relevant area of engineering/science (Control Engineering, Electrical Engineering, Physics, Mechatronics, etc.).
  • Relevant work experience preferably in industry.
  • Practical experience of working with industrial control systems such as PLCs and Variable Frequency Drives.
  • Good programming skills, experience of Python programming and familiarity with C.
  • High degree of autonomy and able to learn new applications and technologies rapidly.
  • Enthusiasm for learning and good communication skills.

Bonus points for these skills:

  • Good understanding and practical experience of system identification and characterisation of electromechanical/dynamic systems.
  • Good understanding of feedback control system design.
  • Experience with industrial standard motor control systems and programming (e.g. PLCs).
  • An advanced degree may be an advantage but is not required.
  • Familiarity with basic Reinforcement Learning techniques for robotics and industrial control.
  • Experience with system identification for modelling of physical systems.
  • Experience/interest in genetic and evolutionary computation techniques.

No specific expertise in AI technologies is required. However, it would be advantageous if you already have an active interest in AI and its potential in control systems. We welcome applicants with non-traditional career paths or equivalent experience. We’re committed to building a diverse and inclusive workplace. We welcome applications from all backgrounds, regardless of race, gender, disability, religion, sexual orientation, or age.

What we offer:

Salary + bonus + equity. Abingdon (Culham Campus) - we offer hybrid working but typically require you to be in the office at least 3 days per week.

AI Control Engineer (Industrial Automation and Mechatronics) in Nottingham employer: Luffy AI

Luffy AI is an exceptional employer, offering a unique opportunity to be at the forefront of the Physical AI revolution in a collaborative and innovative environment. Located at the Culham Campus in Oxford, our team thrives on diversity and inclusivity, providing employees with the chance to influence the company's direction while working on cutting-edge projects that have real-world applications. With competitive salary packages, hybrid working options, and a strong focus on personal and professional growth, Luffy AI is the ideal place for those looking to make a meaningful impact in industrial automation and mechatronics.

Luffy AI

Contact Details:

Luffy AI Recruitment Team

We think you need these skills to ace AI Control Engineer (Industrial Automation and Mechatronics) in Nottingham

Control Engineering
Mechatronics
Industrial Automation
Robotics
Simulation and Modelling
Software Engineering
System Identification