DevJobs

ML Ops Engineer

Overview
Skills
  • Python Python ꞏ 5y
  • GCP GCP
  • Big-data
  • Cloud
  • ML Ops
  • Kubeflow
  • Vertex AI
We’re looking for a strong ML engineer to join our team and help lead the development of our ML infrastructure. If you’re passionate about ML, Python and high-scale big-data environments, come join the team!

What you'll do:

  • Lead the development of our ML Ops infrastructure, creating processes that support ML projects in the company from their development phase until their deployment to production and beyond
  • Build and support an infrastructure for real-time model inference at scale, serving billions of requests each day.
  • Implement data-based processes and solutions processing massive amounts of data as part of our ML pipelines.
  • Work closely with our data scientists to deliver new projects, define processes and coding standards and gather requirements to further develop our infra.
  • Design and implement pipelines integrating ML models and prediction results into our core products.
  • Be the go-to person for any Python or ML Ops related question or idea, being a focal point for both our Research and engineering teams.


Who you are:

  • 5+ years of backend development in Python.
  • Has experience developing ML Ops processes or supporting ML models in production.
  • Experienced with big-data, high-scale environments.
  • Familiar with cloud vendors concepts and tools, preferably working on top of one in prior positions.
  • Team player with good verbal and written communication skills.
  • Passionate about technology, fast learner and eager to lead and take ownership of big projects end-to-end.
  • Prior experience working with GCP - advantage.
  • Experience with Vertex AI and Kubeflow pipelines - advantage.
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