Principal Machine Learning Engineer
Core
Architect, build, and scale the ML platform powering Ping's intelligent identity products, enabling data scientists to train, optimize, and deploy low-latency decisioning models for billions of identities.
Role type
Principal Machine Learning Engineer (Platform & Infrastructure)
Builds
Scalable ML platforms, feature stores, real-time streaming pipelines, and automated MLOps tooling for identity and access management products.
Domain
Cybersecurity / Identity and Access Management (IAM) / Cloud Data Infrastructure
Deliverable
production ML models
Required skills
Python, SQL, Apache Spark, Airflow, Kubernetes, CI/CD, Feature Stores (offline/online), Real-time streaming (Kafka, Flink), Cloud platforms (AWS), Distributed systems architecture, MLOps
Preferred skills
Apache Iceberg, dbt, Deep Learning, LLMs, PyTorch, Multi-account cloud environments
Technologies
Python, SQL, Spark, Airflow, MLflow, Kubernetes, Docker, Kafka, Flink, AWS, SageMaker, Redis
Responsibilities
Architect and manage distributed big-data pipelines; Design and run the ML models' feature store ensuring consistency; Own real-time ML in the critical path with sub-second model serving; Build efficient, automated data pipelines; Drive MLOps end to end including containerized deployment and monitoring; Create tools to reduce overhead for data scientists; Mentor engineers and shape system architecture.
Seniority
Principal, hands-on IC with strategic direction and mentorship
