ML Ops Data Scientist - Remote

Overview

The Lead MLOps Data Scientist will own and rebuild the company’s MLOps platform end-to-end, enabling faster experimentation, deployment, and real-world impact across a strong data science team.

In Short

• Architect and build a 0→1 MLOps platform
• Overhaul CI/CD pipelines for ML workflows
• Reduce model deployment timelines from weeks → days
• Build systems for feature stores, retraining, and experimentation
• Partner closely with Data Science & Engineering to scale ML impact
• Stay hands-on (70–80% coding)

Requirements

• 5+ years in MLOps / ML Infrastructure
• Proven experience owning end-to-end ML pipelines in production
• Experience building from 0→1 OR deep ownership in a mature ML platform
• Strong background in ML orchestration (Kubeflow, Vertex AI, Airflow, etc.)
• CI/CD for ML systems
• Cloud (GCP preferred), Python, SQL
• Experience with recommendation systems, ranking, or personalization
• Strong DevOps fundamentals

Benefits

• High impact: ML already drives the business — this scales it further
• Ownership: true 0→1 platform build
• Lean, strong team: ~5 data scientists delivering real results
• Remote-first with strong comp + equity