Career Opportunities
Graduates of the Programme will be able to start a career in Computer vision and Machine Learning and apply for the positions of:
- Computer Vision Software Engineer,
- Perception Engineer,
- 3D Perception/Computer Vision Algorithm Engineer,
- Computer Vision Testing Engineer
- Computer Vision Scientist
Alexander, program graduate
— Why did you choose this particular educational program?
— Throughout my professional career, I've always maintained a keen interest in related fields, particularly computer vision and the applied problems it solves. Early in my journey, I frequently encountered such practical challenges, but my knowledge was fragmented - the fast pace of work sprints rarely allowed for deep theoretical immersion or systematic study of the field.
When this program launched, it immediately caught my attention. The Higher School of Economics is one of Russia's most prestigious universities with a strong faculty, and the opportunity to gain fundamental knowledge through such a program seemed like an excellent chance to fill gaps in my understanding and systematize my experience.
— What attracted you most about this program?
— At that time, I really needed an academic "shake-up" - I wanted to set myself a serious goal and have the opportunity for prolonged, focused, systematic work within an educational framework. I sought not just to acquire new knowledge, but to deeply immerse myself in one of the areas that had long fascinated me.
I was particularly drawn to the course topics outlined in the program. Even during my initial review of the curriculum, I saw interesting and relevant problems I wanted to explore in depth - including image colorization, neuron activation visualization with Grad-CAM, heuristic lung image segmentation, generative models, and neural network applications on mobile devices.
— How did the program help develop your technical and professional skills?
— The program contributed significantly to my development - both technical and professional. First and foremost, it helped me rethink and structure my approach to learning: I became more deliberate in how I tackled new subjects, paying attention not just to practice but also to fundamental aspects.
Courses related to image processing and machine learning provided a solid theoretical foundation that I could immediately apply in practice. Each subject proved valuable in its own way - whether algorithms, modern research methods, or approaches to neural network training.
Moreover, many assignments were designed to encourage not just repetition of learned material, but the development of independent engineering thinking and research methodology. This became excellent skills training.