ML Ops Data Scientist (Remote)

Map Ssg

1d•$170,000 - $206,000•Remote

About The Position

We’re working with a high-growth, profitable consumer platform that’s already driven meaningful revenue impact through machine learning and is now investing heavily in scaling its ML infrastructure. This is a foundational hire — you’ll 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. The Role You’ll act as the technical owner of MLOps, leading the design and build of next-gen infrastructure that powers model training, deployment, and iteration. 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

Responsibilities

Act as the technical owner of MLOps, leading the design and build of next-gen infrastructure that powers model training, deployment, and iteration.
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)