Huawei is looking for qualified candidates to join their growing Machine learning team in Moscow R&D Centre. Team’s focus is to provide the best in class algorithm development and system solutions for various lines of business of Huawei. As a required theoretical background suitable candidate should be familiar with Data Mining, Machine Learning, and Statistics. Successful candidate should have extensive software development experience.
- Successful candidate demonstrates an ability to do scientific/engineering research both as a team member and as a single player
- Preference will be given to candidates with scientific degrees (Ph.D., Dr.Sc.) with publications in relevant areas such as Probability, Statistics, Stochastic, etc.
- Preference will be given to candidates with relevant working experience, especially in industry applications.
Absolutely necessary skills:
- Machine Learning techniques: supervised and unsupervised, transfer learning
- Probability theory and statistics: Bayesian Networks, Statistical inference, etc.
- Experience with programming languages such as Python, C/С++
- Experience in simulation tools such as MATLAB, R, etc.
Other skills that will be considered as a plus:
- Times series analysis: ARMA, Kalman filter, DSP
- Communication protocols: MAC, RLC, TCP/IP, Routing (such as OSPF, BGP etc.)
- GEO data base and algorithm skills
- A typical assignment would be to develop methods of automatic intelligent processing of data sets which characterize different aspects of a complex telecommunication network and to investigate the features of this network applying deep research methods.
- This is a research work, not software development. Only candidates with proven ability in research (scientific or engineering) are invited to apply.
- Systems activities include theoretical analysis, computer aided analysis, regular active participation in design and review sessions, contribution to Huawei's IP portfolio and systems support for implementation related activities.
- Candidates will work in an exciting team environment with some of the brightest systems engineers in the industry and will have frequent interaction with other engineering disciplines.
- Senior candidates may lead a team of multiple systems engineers or a multi-disciplinary project.
Moscow, Алтуфьевское шоссе, 1к7, м. ВладыкиноПоказать на карте
Полная занятость, полный день