We are looking for a Machine Learning Engineer to join our Search Engine team in Amsterdam
The Search Team in Huawei’s Amsterdam R&D Center is building an industry-leading Cloud Search product that powers the search experience on Huawei mobile phones. The team is responsible for advanced components of the search engine, including question answering, offline document analysis and machine translation. We are looking for a Machine Learning Engineer to join our team and together build the future of search.
Our mission is to build a state-of-the-art search experience using the latest techniques in information retrieval, machine learning and natural language processing. We maintain active collaboration with local universities to push the envelope on search and deliver the best customer experience.
You will work within a fast-paced team of applied scientists and engineers. You will contribute to optimizing algorithms, building pipelines and data structures to automate the machine learning lifecycle and help maintain a positive team culture. Your responsibilities will include:
Apply the latest, bleeding-edge advancements in ML research to create state-of-the-art technologies.
Design, develop, optimize and test Natural Language Processing pipelines for language understanding.
Work together win a team of applied scientists and machine learning engineers in an agile team
Degree in Computer Science, Physics, Mathematics or related field
Strong background in machine learning theory and practice with at least 3 years of hands-on experience implementing and deploying large scale machine learning systems.
Experience in Natural Language Processing or Information Extraction
Strong understanding of system design, data structures and algorithms
Proficiency in multiple programming languages, preferably Python, Java and Golang
Experience with a deep learning framework like PyTorch or Tensorflow.
Experience with ElasticSearch, Spark, Hive, Hadoop or other big data technologies
Excellent communication and collaboration skills
Level of experience (years):
Mid Career (2+ years of experience)