Machine Learning

Future and career

The demand for engineers and scientists with expertise in Machine Learning is growing, driven by the increased availability of data, the increasingly powerful ML models, and their applicability across a wide range of domains and industries. After graduation, you can pursue a career in industry, at a start-up or in a traditional, well-established company. Graduates work as software developers, deep learning engineers, computer vision engineers, data analysts, software engineers, quantitative analysts, data scientists and systems engineers in companies such as Dice, Logitech, Google, and McKinsey in, for example, Sweden, Switzerland, Germany, China, India, and the US.

This master's programme is also a suitable basis for work in a research and development department in industry, as well as for a continued research career, and doctoral studies.

Discover alumni from the programme Martha Vlachou Software Engineering Manager at Ericsson Christian Ryan Member of Technical Staff at Anthropic Deepa Krishnamurthy Mentor in MIT's Applied Data Science Program at Great Learning Romina Arriaza Machine Learning Engineer at Tracab Interviews with graduates from Machine Learning Find more graduates from Machine Learning on LinkedIn

Sustainable development

Graduates from KTH have the knowledge and tools for moving society in a more sustainable direction, as sustainable development is an integral part of all programmes. The three key sustainable development goals addressed by the master's programme in Machine Learning are:

Advancements in Machine Learning are increasingly influencing many facets of our lives and are expected to have a growing impact on society. On the one hand, it can render many blue-collar and white-collar jobs obsolete due to increased automation. However, it also has the potential to, for example, enhance patient outcomes through more personalised medicines and diagnoses. Some of these developments may not benefit everyone in society or could have unintended consequences.

Graduates of the programme are well informed about the technical capabilities and potential applications of Machine Learning and well-positioned to push the advancement of Machine Learning/AI further. Thus, as part of the programme, and within KTH, we highlight the ethical issues and responsibilities of these skills and knowledge in mandatory courses such as the Program Integrating Course in Machine Learning (DD2301) and Artificial Intelligence (DD2380). We see these responsibilities as being aligned with the UN Sustainable Development Goals, where we specifically promote awareness of the SDGs as part of “DD2301: the Programme Integration Course" and also highlight the use cases of “AI for good", which intersect with the SDGs, such as in the design and operation of wind and solar farms to make them more efficient, the diagnosis and treatment of various diseases and the design of health interventions, and precision engineering to promote more efficient farming practices.

In the final year of their studies, students from the programme will have an opportunity to complete final degree projects that are highly relevant to multiple SDGs. Examples of where such projects took place in the past are: