Huawei is a leading global information and communications technology (ICT) solutions provider. Driven by a commitment to operations, ongoing innovation, and open collaboration, we have established a competitive ICT portfolio of end-to-end solutions in Telecom and enterprise networks, Devices and Cloud technology and services. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 197,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.
Huawei's Munich Research Center is responsible for advanced technology research, architectural development, design and strategic engineering of our products.
The size of our cloud platform is gaining momentum and it is already planet scale. Huawei Cloud is one of the largest and fastest-growing platforms in the world. It has strong presence with over 40 availability zones located across 4 continents and 23 geographical regions, covering locations such as Germany, Hong Kong, South Africa, or Brazil, among others.
Now we are looking for a:
(Senior) Machine Learning Engineer/Researcher (m/f/d)
Our team’s mission is to develop new intelligent tools aimed at SRE and cloud maintenance operators to enable them to quickly detect anomalies thanks to the use of artificial intelligence when cloud services are slow or unresponsive. We analyze observability data from Huawei Cloud to detect glitches which impact customers, identify their root cause within seconds, and automatically fix problems, when possible.
If you are enthusiastic about tackling real-world problems which require engineering and theoretical approaches to be solved, and you love to work with a dynamic group of people driven by challenges, come and join us!
To drive reliability, we are seeking for a (Senior) Machine Learning Engineer/Researcher to join the Ultra-scale AIOps Lab which is distributed across Dublin, Munich, and Shenzhen Research Centers. This team is entrusted with developing key data mining and machine learning algorithms for Huawei Cloud. You will take systematic approaches to solve operation problems, dissect how large-scale, complicated systems work, and feel a great satisfaction from making continuous improvements.
- Use deep learning and machine learning to create scalable solutions for business problems
- Develop new tools using cutting edge technology focusing on efficiency and automation
- Work closely with the AIOps team to jointly develop innovative tools driven by AI
- Build ML systems in production settings
- Collaborate with colleagues from science, engineering, and business backgrounds
- PhD in Computer Science or related fields
- Extensive years of experience as an ML, data scientist or data engineer
- Experience with statistical software (e.g., Pandas, R) and programming languages (e.g., Python, Java).
- Hands-on expertise with ML libraries (e.g., Scikit-Learn, TensorFlow, Keras)
- Experience with applying machine learning on large-scale datasets.
- Experience with fast prototyping
- Demonstrated ability to solve challenging engineering problems is required.
- Fluent written and spoken English.
By applying to this position, you agree with our RECRUITMENT PRIVACY STATEMENT. You can read in full our recruitment privacy statement via the link below.
What you can expect
- Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
- We offer you a competitive compensation package and a broad range of training opportunities. Many online and face-to-face training programs.
- Self-responsible work in a competent, motivated and constantly growing team.
If you are enthusiastic in shaping Huawei’s Munich Research Center together with a multicultural team of highly skilled Engineers and Researchers, feel free to contact us. Driving future technologies focused on the customer experience is our main mission. Apply now!
Please send your application and CV (incl. cover letter and reference letters) in English.