Machine Learning Architect

Apply now

Machine Learning Architect

We are looking for an experienced, resourceful Machine Learning Architect to drive Inspera’s machine learning strategy and its platform architecture. You will build a multi-disciplinary team of Data Scientists and Engineers to develop reliable predictive models for learning analytics.

For more than a decade, our high-stake customers have collected banks of structured data from standardised tests. These banks now await your analysis in pursuit of improving teaching and learning. You are passionate about data and analytics and want to use cloud technology and AI to impact global education. You will play an essential role in shaping the long-term vision and strategy to re-invent educational assessment for the 21st century.

FULL-TIME · OSLO, NORWAY

Job responsibilities

As Machine Learning Architect your responsibilities will be to:

  • define the strategy & roadmap for analytics / deep learning frameworks and evangelise the vision to the organization
  • demonstrate technical leadership and ability to contribute to establishing the overall solution direction
  • build a world-class team of data scientists and engineers to do data mining and apply predictive learning analytics
  • work in conjunction with Growth, Services, Product, DevOps, Engineering and QA teams to drive the strategy, research and experimenting

  • design, document and lead the implementation of software and systems to help ensure optimal implementation of the neural network models, real-time analytics with assessment data
  • design, develop and implement Machine Learning analytics technology stack for prescriptive and predictive analytics

Job requirements

Our ideal candidate will have a both a software engineer background combined with a machine learning experience along with strong work ethic.

We are searching for applicants with:

  • MS degree in Computer Science or related quantitative field with 5 years of relevant experience or Ph.D degree in Computer Science or related quantitative field
  • experience in one or more of the following areas: machine learning, large-scale data mining or artificial intelligence
  • proven ability to translate insights into business recommendations
  • experience with distributed computing frameworks such as Yarn, Kubernetes, AWS ECS
  • experience with Docker, Orchestration
  • experience with ML frameworks – TensorFlow, Caffe2, MxNet, H20, PredictionIO, CNN, RNN, Torch, Java, Scala, Python, R, CUDA, OpenCL
  • experience developing and debugging in Java/Scala/R/Python, knowledge of functional programming
  • experience with Spark ML/Hadoop is a plus
  • experiences with AWS infrastructure is a plus