Remote MLOps Engineer

Remote
Roles:
Machine Learning
Must-have skills:
PythonDockerKubernetes
Nice-to-have skills:
AWSElasticsearch
Considering candidates from:
Europe, Turkey and United Arab Emirates
Work arrangement: Remote
Industry: Technology, Information and Internet
Language: English
Level: Middle or senior
Required experience: 2+ years
Size: 51 - 200 employees
Logo of Klevu

Remote MLOps Engineer

Remote
Klevu creates an intelligent site search solution designed to help eCommerce businesses increase onsite sales and improve the customer online shopping experience. The company produces mass amounts of data on a daily basis. Combined with shopping data being directly delivered to their backend systems with access to shopping catalogues containing both the structured attributes and unstructured product descriptions, they have a wealth of data with immense opportunity to extract valuable insights and improve search accuracy.
Tasks:
  • Work closely with the AI team members from research to development
  • Helping with distributed experimentation infrastructure, collaborating with other teams to define APIs and implementing them for the models developed by the AI members, testing and deploying them on cloud instances, and also scaling these as needed.
Must-have skills:
  • Writing clean, understandable and easily maintainable code
  • Strong programming/software engineering background enabling rapid codebase acquisition and scalable development in Python (2+ years background in the development and 2+ years in ML)
  • Hands-on experience on Docker and Kubernetes
  • Cloud experience, AWS preferred
  • Experience in deploying and scaling Tensorflow and Pythorch models
  • Experience with MLops tools such as MLflow
  • Excellent oral and written communication in English
Nice-to-have skills:
  • Technical understanding of overall eComm platforms
  • Experience of working with Solr, Elasticsearch or similar search technology
  • Experience with Grakn or Neo4j
Interview process: 
  1. Intro call with Toughbyte
  2. First technical interview 
  3. Test assignment
  4. Most probably there will be another tech interview
  5. Final culture fit interview with the CEO