Are you passionate about high-end technological design? Do you want to continue developing your skills with a combination of education and work?
The Professional Doctorate in Engineering (PDEng) programme Business & IT (BIT) offers you a 2-year position combining post MSc education and a design project to be carried out at video service provider Divitel in Apeldoorn.
The educational programme, carried out at the University of Twente in Enschede, will have an in-depth and broadening character with ample attention for professional development and will be partly tailored to the design project. In collaboration with Divitel in Apeldoorn you will work on high level, creative new designs for complex issues.
The challenge & the project
The key challenge in providing digital video services lies in video delivery ecosystems’ complexity and dynamic nature. Manually sorting out logs, metrics, events, and alerts, diagnosing the causes of incidents and anomalies, then taking actions to correct quality issues require much human interaction and effort. This impacts service quality negatively, resulting in low Net Promoter Scores, low viewer satisfaction, high costs of operations, and high customer churn.
The typical Video Service Provider wastes a significant portion of its budget on inefficiencies that only worsen as complexity grows. The complexity of ecosystems continues to grow, and the number of ecosystem elements needing to be managed multiplies exponentially as technologies such as cloud migration take hold. Divitel wants to address this problem and bring an automated solution to the marketplace.
The vision is to automate video delivery operations resulting in a SaaS solution that includes a suite of tools that monitor, alert, and predict, which is also integrated into the decision-making process by providing insights about current conditions and receiving continuous feedback. When deployed commercially, it shall detect and fix service failures in just minutes instead of weeks or months. In addition, it will learn over time, becoming increasingly intelligent with each failure detected and will detect and fix problems in real-time. This way, a contextual resiliency and a high level of automation will be reached, where machine intelligence mostly makes decisions and executions. The solution will significantly increase video service providers’ service quality, customer satisfaction, and operating margin.
Your goal is to design a framework and deliver a prototype implementation that efficiently and effectively collects data from various video delivery ecosystems and makes the data ready for machine learning and analytics. You will develop a data pipeline and data warehouse, and it will also have the intelligence to discover data sources, capture interactions between ecosystem elements, and map their interdependencies. This intelligence shall auto-discover the connected components in the environment and dynamically create a topology to visualize the connections across the entire ecosystem. With these, the solution can discover the functional dependencies within the video delivery workflows.
- You hold a MSc degree in:
- Computer Science
- Internet Science & Technology
- Software Technology
- Business Information Technology (BIT)
- Industrial Engineering and Management
- Interaction Technology,
- or a related specialisation
- You have knowledge of software development and operations (tools, collaboration, experience);
- Analytics knowledge or willingness to learn;
- Knowledge of programming languages (Python or similar);
- You have demonstrated affinity with design and multidisciplinary assignments;
- You have a passion for finding solutions for complex IT-related issues;
- You have excellent collaboration and communication skills;
- You are self-starting and self-motivating, willing to take initiatives and feel the responsibility for your own project;
- We prefer a candidate with strong data science, machine learning, and cloud engineering expertise for architecting and engineering AI/ML solutions in the domain of video delivery networks
- Identify and define how to apply machine learning to technical and business challenges
- Identify and define separate sub-projects and break them down to project steps
- Develop machine learning solutions to solve the identified challenges
- Put them into production and build the necessary MLOps infrastructure
- Support refinement of the technical cloud architecture (including pipelines, model deployments, etc.)
- Guide a team of data engineers and machine learning engineers in data processing, cleaning, feature engineering, and machine learning modeling
Applicants with a non-Dutch qualification and who have not had secondary and tertiary education in English can only be admitted with an IELTS-test showing a total band score of at least 6.5, internet TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE).
University of Twente and Divitel offer you a very challenging position for two years in an inspiring multidisciplinary and international environment. In this time we will provide you with a tailor made post-master design programme that has an educational component (~50%) as well as a design project (~50%). You will be supervised by a team of experts from both Divitel and the University of Twente. The salary will be € 2.009,- gross per month.
If you have completed a HBO / WO ICT training, please contact us quickly.
As a member of the NL AI Coalition, Divitel is committed to contribute to the development of AI in the Netherlands. The Dutch AI Coalition aims to stimulate, support and organize the Dutch activities in AI.