Atypon () is a software and services company headquartered in Silicon Valley, California, renowned for its technological leadership when it comes to online delivery of professional / scholarly publisher content.
We are the market leader in content delivery for scientific, technical and medical publications.
We are looking for a talented and experienced recommender systems engineer to join our R&D team. Role involves the collaboration with engineering and product teams to design and develop the new generation of recommender systems to help researchers and scientists know more and achieve more.
You will be responsible for
Exploring, designing and developing effective large-scale commercial recommender systems analyzing contextual and behavioral real-world data
Evaluating and optimizing algorithms through feature engineering, controlled offline and online A / B testing experiments
Optimizing recommended system stability, architecture scalability, and ensuring rapid iteration of algorithm strategy modules
This is an exciting and challenging role, where you will not only have the opportunity to collaborate with worldwide reputational research labs, but also continuously learn and apply cutting-
edge technologies in academia and industry to continuously build and optimize information retrieval and recommendation systems in order to improve business objectives, such as information retrieval / relevance (e.
g., precision / recall, DCG), user profiling and effectiveness (e.g., conversion / click through rate etc).
MUST HAVE :
Hands on experience with design, development and deployment of large-scale commercial information retrieval and recommender systems
In-depth understanding of business development needs, optimizing search and recommendation strategies from a technical perspective
Deep understanding in the well-known collaborative filtering / behavioral data analysis and content-based recommendation algorithms and solutions and familiar with best-
practices in commercial recommender system applications
Familiar with large-scale data mining, machine learning including deep learning, distributed computing and other related technologies, related to recommendation systems, computing advertising, search engines
Deep knowledge and experience in analyzing massive user behavior data and content information to deeply understand user behavior, in order to provide support for algorithms and business scenarios
Hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
Extensive practical experience in manipulating large scale data (data cleaning, data normalization, data linkage).
Team player who enjoys working collaboratively
Fluency in English written and oral
PhD with at least 3 years, or MSc with at least 5 years relevant commercial experience
NICE TO HAVE :
Experience in applying knowledge graphs in recommendation systems
Experience with big data technologies (e.g. Apache Spark, Apache Flink, Apache Kafka, Elasticsearch, Apache Solr, Hadoop, MapReduce, Scalding / Cascading)
Familiar with search algorithms and core technologies, including Query understanding, Recall and ranking algorithms etc
Deep understanding and experience in Text Mining and Natural Language Processing (NLP) in a commercial setting
Familiar with frameworks such as Keras, TensorFlow, PyTorch, sklearn, liblinear, Weka, OpenNLP, etc
Familiar with cloud technologies, such as AWS, Google AI Cloud, etc
Opportunity to grow in a fast moving and dynamic organization with like-minded colleagues
Flexible working hours
Regular performance evaluations based on merit