Machine Learning Engineer

The mission of the Machine Learning team is to empower Schibsted Media to leverage AI and Machine Learning for creating smart and data-driven products and services. We collaborate closely with product and engineering teams to build models and services that add value in terms of, e.g., increased relevance, automation and personalisation. We are now looking for a passionate and exceptional machine learning engineer with experience of building machine learning systems that bring real value. 
 

Responsibilities  Join a team of talented and motivated data scientists and engineers based in Oslo and Stockholm Develop impactful machine learning based services and products within the areas of personalisation and recommendation, predictive modeling, and automation, in close collaboration with product and engineering teams primarily within Schibsted Media Initiate and lead projects from idea to completion. Talk to product managers, business people and your peers to get an understanding of the project requirements. Take part in ideation, prototyping, and then write production code to train and serve machine learning models using latest tools and frameworks within ML and AI. Engineer and implement scalable systems and services around the models, using best development practices and state-of-art patterns and tools. Continuously monitor the quality of the systems, design measurements to monitor their health (both the engineering systems and data quality) Help defining and continuously improve our development environment, and communicate the best development practices within the organization (i.e., code reviews, testing, etc) Learn a lot and share your own knowledge. Travel occasionally, either to meet colleagues and work together, or to attend conferences 
 
Relevant Skills and Experience  Masters Degree in Computer Science (or similar) Fluent in multiple development languages (static and dynamic) as well as both functional and imperative programming, and interested in learning more. We currently use mostly Python and Scala Deep understanding of systems design, algorithms, and data structures Understanding and genuine interest of AI and machine learning methods and algorithms, e.g., classification, regression, gradient based optimisation and neural networks. Experience of building systems for model training and serving using, e.g., TensorFlow, Keras, or PyTorch Experience with cloud infrastructure, e.g., AWS or Google Cloud, and being familiar with container based architectures and microservices Experience with distributed computing technologies and “big data” technologies like MapReduce, Spark, Hadoop, Kafka, Storm, Cassandra, large scale storage systems 
 
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