Senior MLOps / ML Platform Engineer
Core
Build and maintain production-grade ML orchestration pipelines, model registry workflows, and serving infrastructure for a large-scale AdTech ecosystem processing hundreds of millions of auction requests daily.
Role type
Senior MLOps / ML Platform Engineer
Builds
Scalable ML training and serving pipelines, isolated multi-tenant model environments, and real-time optimization workflows for predictive decision-making systems.
Domain
AdTech / Programmatic Advertising / Machine Learning Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python, Kubernetes, Docker, CI/CD for ML, ML lifecycle platforms (MLflow, Kubeflow, Airflow, Vertex Pipelines), ML observability (drift detection, skew monitoring), multi-tenant system design, Infrastructure-as-Code (Terraform), Linux
Preferred skills
Feature stores, large-scale batch scoring, data versioning tools (DVC, lakeFS), low-latency serving databases (Bigtable, Redis, Aerospike), GPU scheduling, compliance (SOC 2, ISO 27001, GDPR)
Technologies
Python, Kubernetes, Docker, GCP, Vertex AI, MLflow, Airflow, Kubeflow, Argo Workflows, Terraform
Responsibilities
Build ML training orchestration pipelines with retries and idempotent execution; Design model registry workflows with versioning and promotion; Develop isolated per-advertiser model environments; Implement shadow mode and champion/challenger deployment strategies; Develop monitoring for feature drift, prediction drift, and train/serve skew; Collaborate on CI/CD and infrastructure automation; Monitor training and scoring costs across tenants.
Seniority
Senior, hands-on IC
