Machine learning engineer

Nordverse 20. Oct 2020 Hlutastarf

Nordverse is a growing health tech startup creating software solutions to untangle the world’s complex health information. Our mission is to empower healthcare professionals in maximizing their time on valuable human care and give people the tools to engage in their own treatment. We create high-quality software originating from clinical experience and focus on real clinical value.


  • Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence.
  • Develop highly scalable classifiers and tools leveraging machine learning, deep neural networks, data regression, and rules based models.
  • Architect efficient and reusable back-end system that enables experimentation and seamless model change.
  • Set up maintainable data pipelines in the cloud.
  • Identify and resolve performance and scalability issues.

Minimum qualifications:

  • Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or artificial intelligence.
  • 3+ years of programming experience.
  • 3+ years of experience with Python and Tensorflow/PyTorch.
  • 1+ years of working with scalable database solutions.
  • 1+ years of experience with cloud environments.
  • 1+ years of experience with Docker and Kubernetes.

Preferred Qualifications:

  • BS/MS in Computer Science or a related technical field.
  • Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Hive/Spark.
  • Expert knowledge developing production level ML products.
  • Experience with natural language processing solutions.
  • Experience with scaling software.
  • Prior experience within the healthcare industry.

Nordverse was formed in 2019 and is based in Gróska. We look specifically for candidates that are eager to participate in diverse projects, shift focus when necessary and are driven to create meaningful software that improves the lives of others. As this is an early opportunity there is great potential for growth.

We’re looking for a part-time employee working approximately 30 hours/week.

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