ML Ops Engineer

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.