Associate Director, MLOps Engineering
Core
Lead the MLOps team to build and scale the infrastructure bridging ML research and massive-scale production for AI-powered pathology diagnostics.
Role type
Senior IC/Lead MLOps Engineering Manager
Builds
High-scale AI training & inference workloads, cloud infrastructure, Kubernetes clusters, and observability pipelines for medical imaging.
Domain
Healthcare AI / Machine Learning Operations / Cloud Infrastructure
Deliverable
infrastructure
Required skills
Kubernetes, cloud computing (AWS/GCP/Azure), workflow orchestration (Airflow/Kubeflow), infrastructure-as-code (Terraform/Helm), petabyte-scale data management, multi-language systems, AI assistant integration.
Preferred skills
PyTorch/Scikit-learn, Spark/Hive/Databricks, MLOps lifecycle management, feature stores, CI/CD for ML, security/compliance in ML systems.
Technologies
Kubernetes, AWS, GCP, Azure, Airflow, Kubeflow, Terraform, Helm, PyTorch, Scikit-learn, Spark, Hive, Databricks, Amazon EMR, CoPilot, Cursor, Claude.
Responsibilities
Develop long-term vision and roadmap for MLOps team; lead and mentor a team of 6-7+ engineers; partner with cross-functional leaders to address bottlenecks; architect compute/storage pipelines for foundation models; modernize inference stack for 5-10x growth; establish system observability metrics; conduct technology refresh audits.
Seniority
Senior, hands-on IC with team leadership