Knowledge-Graph Engineer - renovai

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Knowledge-Graph Engineer

Description

renovai is a fast-growing Visual AI Design startup providing visual commerce solutions for lifestyle brands.

The core of our real-time solutions leverages computer vision and deep learning to decipher decades of design methodology and esthetic approaches, creating the first ever AI based virtual designer.

We are looking for an enthusiastic research engineer, with proven hands-on experience with developing semantic knowledge graphs, to join our growing AI team and be a key member in the ideation and development of our next generation solutions.

The ultimate candidate has hands-on experience with knowledge graph technologies, using platforms such as Neo4j.

Responsibilities:

  • Develop state-of-the-art and novel KGs and algorithms.
  • Working closely with domain experts to build the core Ontology and KG.
  • Develop and implement algorithms to support semantic reasoning and inference.
  • Develop pipelines to assess the performance and robustness of the solution on relevant tasks.
  • Data collection, curation, and management.
  • Keep up with relevant literature and research publications to implement the latest techniques into our solution.
  • Work on a breadth of software frameworks and libraries related to KG.
  • Develop prototype solutions and take part in their deployment to production in cooperation with devops.

Requirements:

  • Masters or PhD in computer science, engineering, or similar areas.
  • Excellent BSc candidates with proven hands-on experience in graph-database will also be considered.
  • +3 years of hands-on experience in knowledge graph development.
  • Passion for knowledge graph is a must!
  • Experience in developing and integrating algorithms in a commercial product.
  • Strong analytical and problem-solving skills: graph theory, probability theory, statistical inference.
  • Semantic understanding in images – a plus.
  • Excellent communication and teamwork skills.
  • Strong programming skills: high proficiency in Python and OOP (Java).
  • Familiarity with cloud technologies such as GCP/AWS.
  • Routinely working with SW development tools, such as Git, Docker, databases.
  • Experience in advanced machine/deep learning methods – advantage.
  • Previous experience in combining textual and visual data – major advantage.

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