Machine Learning Engineer

[NOTE: This is a remote-friendly position!]

What we do:

Knoema is the most comprehensive source of global decision-making data in the world. Our tools allow individuals and organizations to discover, visualize, model, and present their data and the world’s data to facilitate better decisions and better outcomes. They are used by more than half a million people worldwide every month.

We are actively expanding our capabilities in the area of autonomous knowledge building and ontology creation and want you to help. If you want to spend your day pioneering methods to build knowledge graphs, ontologies, taxonomies and the rest of the zoo of models for finding, organizing, and operationalizing relationships among entitles and concepts across numerous fields of data, then Knoema is the right place for you.

Requirements

• Proficiency in developing production-quality code in one or more popular languages
• Experience developing ML projects that deliver customer impact
• Proficiency in common frameworks: scikit-learn, Pytorch, Tensorflow, or Keras.
• Experience with communicating insights and presenting concepts to diverse audiences.

Senior candidates have:

• Experience shepherding projects from initial twinkling of an idea to deployed, monitored and self-training ML products operating in a SaaS platform
• Experience not just working in, but also optimizing software development cycles, data structures and algorithms.
• Mentoring relationships that have nurtured talent to mature and expand a team’s capabilities

We’d be thrilled to know you have:

• Experience with graph machine learning methods, including graph embeddings and graph neural networks
• Experience in graph database development
• Publications at top conferences or in top journals, on our key topics (knowledge graphs, ontologies, taxonomies, etc.)

• Willing to work on a team that believes:
  • Everything starts with the customer
  • Deliver first, optimize soon
  • Small experiments >>> large releases
  • Debates are a sign of passion, and are never personal
  • Ownership is key
• Viewing diversity as a core strength, not just a nice feature
• Embracing a growth mindset to tackle new, interdisciplinary challenges