Principal ML Engineer — Scalable ML Platform Architect

Ping Identity; United States; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Generous PTO & Holidays

Parental Leave

Retirement Programs

Competitive benefits & perks

Global volunteering

Job summary

Ping Identity is hiring a Principal ML Engineer to architect, build, and scale the ML platform powering Ping's intelligent identity products. You will enable data scientists and engineers to train, optimize, and deploy low-latency models that operate in the critical path of billions of identities.

The role blends data engineering, software development, MLOps, and ML automation. You will deliver scalable ML platforms, feature stores, CI/CD, and tooling while collaborating across Data Science,

Qualifications

• 6+ years of experience as an ML Engineer building ML platforms, data infrastructure, and large-scale distributed systems.
• Proficient in Python and SQL; strong experience with Spark or similar frameworks.
• Production experience with Airflow, MLflow, Kubernetes, and CI/CD pipelines.
• Hands-on experience with offline and online feature stores, real-time streaming (Kafka, Flink), and low-latency model serving.
• Experience with public cloud platforms (AWS preferred) and data/ML services; strong communication and teamwork.

Responsibilities

• Architect, build, and operate scalable ML platforms, tools, and services for data scientists and engineers to promote, evaluate, deploy, and monitor models in production.
• Design and run the ML models’ feature store with offline/online consistency, lineage, and governance.
• Own real-time ML in the critical path with low-latency serving in production.
• Build automated data pipelines using Python, SQL, Airflow, and Spark to support training and inference.
• Drive MLOps end to end — CI/CD, containerized deployment on Docker/Kubernetes, monitoring, lifecycle management.
• Create tools that reduce overhead and enable data scientists to focus on model development.
• Architect and manage distributed big-data pipelines (Spark, Kafka, cloud-native data platforms) with high availability.
• Collaborate with Data Science, SRE, and Product teams to integrate ML capabilities into Ping's ecosystem.

Skills

Python programming

SQL programming

Distributed computing

Team collaboration

Problem solving

English communication

Education

M.Sc. in the applied science field

Tools

Python

SQL

Spark

Kubernetes

Docker

Airflow

MLflow

SageMaker

Job description

Ping Identity is hiring a Principal ML Engineer to architect, build, and scale the ML platform powering Ping's intelligent identity products. You will enable data scientists and engineers to train, optimize, and deploy low-latency models that operate in the critical path of billions of identities.

The role blends data engineering, software development, MLOps, and ML automation. You will deliver scalable ML platforms, feature stores, CI/CD, and tooling while collaborating across Data Science,