ML Ops Engineer

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.