The Advanced Digital Design and Manufacturing (ADAM) project seeks to accelerate the Airbus transition towards a future of digital design and manufacturing. The team is uniquely positioned to identify and innovate on emerging technologies with collaborators in Silicon Valley and across the globe. ADAM provides a platform to drastically reduce Aerospace product lead-times and production costs. Through our tool-agnostic framework, we integrate existing and newly developed software solutions. We provide easy-to-use tools to design and automate processes in aerospace manufacturing.
A³ by Airbus is the Silicon Valley outpost of Airbus. The mission of Airbus is to make things fly. Our job at A3 is very simple: we seek to disrupt Airbus (and the competition) before anyone else can. And in the process, we are setting out to build the future of flight.
At A³, we execute projects and foster partnerships. Projects are ambitious, risky, time-constrained undertakings that culminate in a demonstration at convincing scale—something that’s more than a mere prototype, but somewhat short of a product. One project is focused on advanced digital design and manufacturing processes and tools.
Your role as a Software Engineer will be to assist the Engineering Leads in executing a work package for an A³ project with a focus on speed, quality, and cost. You will need to understand the analytic framework and business case the project is based on and advocate it within groups internal to and external to the project. You will be responsible for the development of algorithms that enable understanding of engineering designs, manufacturing, and in-service data to improve the speed and quality of Airbus services and product design.
To get specific, your responsibilities will include:
- Designing, training, and tuning state of the art deep learning models and algorithms to analyze 3D geometry, manufacturing process data, engineering documentation, supply chain, and aircraft in-service data
- Analysis of large amounts of historical data, including data clean-up, pattern identification, selection of sampling criteria
- Driving the efficient implementation of these algorithms within the server environment at A3 and Airbus
- Interfacing with external research groups supporting our model development
- Implementing tests to validate the findings of the deep learning algorithms
- Participation in code and architecture reviews as required
- Development of documentation for software written
- Close collaboration with partners across the wider Airbus group to quickly establish Proof of Concepts to resolve operational Use Cases, and provide expertise on roadmaps towards industrialized solutions.
We expect that you will have:
- An advanced degree in Computer Science, Statistics, Engineering, Mathematics or a related field.
- A demonstrated track record in developing algorithms for data analysis using TensorFlow, PyTorch, Caffe or another common framework
- Prior experience in preparing data for analysis, building predictive models, and
- Expertise in Python, Java, or C/C++
- Drive and curiosity to research new modeling & analysis techniques and suggest improvements to the team
In addition, the following skills and qualifications will be an advantage:
- Expertise in developing for GPU computation
- Experience in optimizing deep learning models
- Software development experience in a production environment
- Passion for increasing the productivity of engineering teams
- Ability to work under pressure to meet sometimes aggressive deadlines
To succeed in this position, you need to be willing to work with a flexible schedule including travel.
By the way, you might be interested to know that we offer a killer benefits package as well as a flight training benefit, just in case you don’t already have your pilot’s license!
A³ by Airbus is an equal opportunity employer in every category. The data is incontrovertible that diversity leads to better teams, better performance, and better results. Consequently, we actively seek candidates of all genders, backgrounds, and experiences.