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Graduation internship: AI driven documentation analysis

Posted 25 May 2024
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Work experience
0 to 1 years
Full-time / part-time
Full-time
Job function
Degree level
Required languages
English (Fluent)
Dutch (Fluent)

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Assignment

In our organization, we provide various software components for our automated warehouse solution. Each of these components comes with its respective documentation, including vital information such as Kafka events, REST APIs, sequence diagrams, deployment instructions, configuration keys, and release notes. The challenge we face is that it can be quite challenging for our testing and support teams to quickly find the information they need within this documentation. This difficulty arises because we use different versions of the software components, and the terminology or language used in the documentation can vary as well, causing confusion when resolving issues.

This issue arises due to our continuous efforts to improve our software and release new versions. Each new version introduces changes and enhancements, and the documentation may use different terminology for the same concepts, leading to confusion.

This issue has a twofold impact. Firstly, it hinders the efficiency of issue resolution, potentially disrupting our warehouse operations. Secondly, it places an increased workload on our support teams as they spend more time searching for information within the documentation, leading to higher support costs.

The objective of this internship is to explore the world of AI to make issue resolution in our system more efficient. Interns are encouraged to investigate and experiment with various AI techniques and technologies that can help address the challenges posed by diverse terminology and multiple versions of documentation artifacts we have.

Your research should aim for a future where we no longer need to rely on a large team to investigate and debug problems. Instead, we can rely on AI to analyze issues using the proper documentation. Your research should result in a Minimum Viable Product that demonstrates the potential of AI in this context.

As part of this assignment, we also require a roadmap for taking the MVP solution to the next level. This extended solution should include the automatic analysis of logged data, further supporting our testing and support teams. Your findings and recommendations should lay the foundation for a practical and comprehensive AI-driven tool that not only streamlines issue resolution but also proactively handles logging analysis. This assignment provides a unique opportunity to explore the transformative potential of AI while solving a real-world problem within our organization, specifically for our automated warehouse solution.

Department

Vanderlande is a global market leader in material handling systems and innovation is the key to winning in a world that is changing faster than ever, which is why it is essential for Vanderlande to develop cutting-edge solutions. The use and development of cutting-edge technologies is core to that success. This technology alone does not make a successful organization and our mantra is “In a world of technology, a belief in people”. Within the Development Centre Software (DCS) departments you can be one of those people and bring your passion for cutting-edge technologies and have an opportunity to make a positive impact to some of the world’s leading companies that rely on Vanderlande to give them a competitive advantage. The software and solutions that we create are at the core of driving the equipment and processes that make this happen. Be a part of the team that is creating software that is being used in hundreds of the world’s leading organizations worldwide.

As intern you will work in a team of experienced software architects that lay the foundation of the nonfunctional technology roadmap for the warehouse platform.

Tasks / Responsibilities

  • Research AI techniques.
  • Develop an MVP solution.
  • Data collection and processing.
  • Problem solving.
  • System thinking.
  • Roadmap creation.

Your Profile

  • Java / Spring Boot knowledge is crucial.
  • Familiarity with Docker is essential.
  • Basic knowledge of Kubernetes and Azure.
  • A fundamental understanding of AI and machine learning concepts is essential.
  • Data analysis will be needed to work with AI.
  • The ability to conduct research and learn new technologies.
  • Mandatory enrollment to a Dutch Education System & resident of The Netherlands.

Vanderlande is the global market leader for value-added logistic process automation at airports, and in the parcel market. Vanderlande’s baggage handling systems move 4.2 billion pieces of luggage around the world per year. Its systems are active in 600 airports including 14 of the world’s top 20.

Logistics
Veghel
6,000 employees