AI Research Engineer -Specializing in Recomendation System

Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices.

We have more than 194,000 employees, and we operate in more than 170 countries and regions, serving more than three billion people around the world.

Our vision and mission are to bring digital to every person, home, and organization for a fully connected, intelligent world.

To this end, we will drive ubiquitous connectivity and promote equal access to networks; bring cloud and artificial intelligence to all four corners of the earth to provide superior computing power where you need it when you need it; build digital platforms to help all industries and organizations become more agile, efficient, and dynamic; redefine user experience with AI, making it more personalized for people in all aspects of their life, whether they’re at home, in the office, or on the go.

As Huawei Türkiye R&D Center, we are now looking for Junior/Mid/Senior AI Research Engineers to join our ranks.

Essential technical requirements:

A. Basic computer science and programming languages

• Experienced in developing and deploying deep learning models, especially in the areas of recommender systems, NLP or computer vision.
• Proficiency in Python programming language is mandatory, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras. (Experience with TensorFlow is a plus)
• Strong analytical and problem-solving skills to translate business requirements into technical solutions.
• Proactive and self-motivated mindset with a keen interest in staying updated with the latest advancements in deep learning and recommendation systems research.

B. Machine Learning

• Solid understanding of neural network theory, including concepts such as optimization, linear algebra, loss functions, etc.
• Familiarity with modern machine learning concepts and architectures.

 C. Recommender System, related NLP and Computer Vision fields

• Strong understanding of recommendation algorithms such as collaborative filtering, content-based filtering, matrix factorization, and deep learning-based approaches.
• Proficiency in data preprocessing techniques, evaluation metrics, and practical experience in deploying and optimizing ML models in production environments.
• Experience in NLP tasks (e.g., vector semantics, entity labeling, text classification) and/or Computer Vision tasks (e.g., classification, detection, segmentation, OCR).

D. Working efficiency

• Proficiency in version control systems like Gitlab or Github.
• Experience with Docker for building a simulation of the production environment.
• Demonstrated expertise in data preprocessing techniques, feature engineering, and data augmentation to enhance model performance. Experience with Apache Spark or Hadoop and SQL proficiency is advantageous.

E. Academic

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field. Advanced degrees (Master's or Ph.D.) are preferred.
• Experience in publishing research papers, contributing to open-source projects, or participating in relevant conferences and workshops is highly desirable.
• Being published in reputable journals related to recommender systems (e.g., ACL, SIGIR) is a significant plus.

Essential non-technical requirements:

• Fluency in English, both written and spoken.
• Ability to work effectively in a multi-disciplinary and multi-cultural team environment.

• A real job from day one: We offer you a professional career in one of the leading multinational technology company.
• Local & international: Reaching more than 190 countries, Huawei is a successful and respected business. We focus on the needs of local costumers by harnessing global expertise and team work. For you, that means exceptional exposure and experience.
• Great Development Opportunities: We'll support you every step of the way, with hands on experience which includes functional, cross functional and international rotations.
• Fast growth and ambitious vision.
• Learning and Development opportunities.