About this job

An exciting opportunity has become available at Leonardo in Edinburgh for a highly motivated systems engineer to join the Model Driven Engineering, Modularity and Re-use (MDEMR) team and lead a number of model-based activities and capabilities. This role will focus on leveraging Graphical Processing Units (GPUs) for accelerated processing and also cover development environments and hardware specifically for Artificial Intelligence and Machine Learning.

This will cover some of the latest engineering capabilities ranging from Requirements management to Continuous Integration and Continuous Delivery whilst utilising an Agile workflow where possible.

Background

A number of GPU activities have been ongoing for the past 18 months in the Model Driven Engineering, Modularity and Re-use (MDEMR) team. There is a GPU strand in the UK wide MDE strategy however this is to be expanded slightly to also support the Artificial Intelligence and Machine Learning UK strategy controlled by our divisional CTO. The main AI and ML focus for this role will be hardware to support AI and ML solution implementation along with toolsets and development best practice. This should integrate with our main modelling toolsets to support traceability of designs from high level requirement definition to low level implementation and “In the Loop” testing. The initial focus will be in Edinburgh however this is expected to branch out to the Luton, Basildon and Southampton sites as the MDEMR team is UK wide with team members at each site.

Responsibilities

• Engage with multiple IPT and CDT engineers to identify opportunities for leveraging GPU hardware for simulation and data processing acceleration and future embedded solutions.
• Own and maintain the GPU development strand of the dynamic MDE process (UK).
• Create and maintain in-house reference designs to promote new techniques and design guidelines for GPU, AI and ML.
• Management of the Edinburgh MDE, Modularity & Re-Use SharePoint (Systems) to promote knowledge sharing for GPU, AI and ML.
• Assist in technical tasks related to the main MDE, Modularity and Re-Use strategy.
• Promote a culture of best practice and knowledge exploitation within IPTs and CDTs.
• Liaising with engineers from all engineering disciplines.
• Assist in the arrangement of in-house training to promote key capabilities.
• Engage with internal domain experts to identify potential use cases for GPU, AI and ML development tools and deployable hardware.
• Attend various seminars when required focussed on GPU, AI and ML development hardware and toolsets.

Profile

Qualifications

Relevant degree (BSc, BEng, MEng, MSc, PhD) in Engineering, or equivalent.

Knowledge

• It is desirable that the candidate has some experience of the MATLAB and Simulink toolset from Mathworks although this is not essential.
• It is highly desirable that the candidate has experience in version management, creating technical documentation and practical experience of creating models from a variety of modular subsystems.
• It is desirable that the candidate has some experience in processing hardware and methods used to deploy auto-coded solutions to lab hardware (CPU, FPGA or GPU).
• It is desirable that the candidate has some experience of AI or ML toolsets including data management, neural networks, training schemes and application build / deployment. Full stack development skills would also be advantageous in this area.
• Knowledge of coding standards (D0178, D0254) is beneficial.
• Knowledge of methods for requirement engineering, including traceability to models with options for automated testing is beneficial.

Skills

In addition to the necessary engineering expertise the applicant should have good interpersonal skills and, preferably, experience of working with multiple engineering disciplines covering systems, software and firmware.

Additional Information

• This role requires the use of Display Screen Equipment.
• This role may require travel around Leonardo sites within the UK and Italy.