Top Tech Jobs & Startup Jobs

Build and operate production-grade ML services and large-scale feature pipelines (Databricks/Spark, Snowflake, Azure). Own model lifecycle (MLflow, CI/CD, retraining, monitoring), activation/integration to DSPs/CDPs/clean rooms, and privacy-by-design patterns. Mentor engineers and set engineering standards.

Convert data‑science prototypes into production ML services; build and operate Databricks/Spark pipelines reading/writing Snowflake; manage full model lifecycle (MLflow, CI/CD, retraining, drift monitoring); deliver/version audience segments to ad‑tech partners; ensure scalability, cost efficiency, privacy, and mentor engineers.

Administer and maintain RHEL and OpenShift clusters on bare-metal, manage node lifecycle and storage, apply patches/upgrades, monitor cluster and hardware health, support IBM Watson/Cloud Pak deployments, coordinate vendor and colo support, implement backup/DR, security hardening, incident response, and produce documentation and runbooks.

Administer and maintain RHEL and OpenShift clusters on bare-metal, perform patching/upgrades, manage node lifecycles and storage (Ceph/ODF, NFS, SAN), monitor cluster and hardware health (Prometheus/Grafana, iDRAC), coordinate colocation/vendor support (Dell, IBM), support IBM Cloud Pak/Watson deployments, implement backups/DR, apply security hardening, troubleshoot incidents, and document runbooks and procedures.

Administer and maintain RHEL and OpenShift clusters on bare-metal, manage node lifecycle and hardware (Dell), apply patches/upgrades, monitor cluster and hardware health, support IBM Watson/Cloud Pak deployments, manage storage and backups, implement security hardening, coordinate vendor and colocation support, document runbooks and perform incident response.