Principal Machine Learning Engineer

📋 Job Overview

Join us on Ping Identity's AI & Data Platform team as a Principal ML Engineer where you will architect, build, and scale the ML platform that powers Ping's intelligent identity products, enabling data scientists and engineers to train, optimize, and deploy low-latency decisioning models that run in the critical path of billions of identities. This role requires a multidisciplinary approach, combining expertise in data engineering, software development, MLOps, and ML automation.

🏢 About Ping Identity

At Ping Identity, we believe in making digital experiences both secure and seamless for all users, without compromise. We call this digital freedom. And it's not just something we provide our customers. It's something that inspires our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it.

Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. Without friction. Without fear.

While protecting digital identities is at the core of our technology, protecting individual identities is at the core of our culture. We champion every identity. One of our core values, Respect Individuality, reminds us to celebrate differences so you are empowered to bring your authentic self to work.

We're headquartered in Denver, Colorado and we have offices and employees around the globe. We serve the largest, most demanding enterprises worldwide, including more than half of the Fortune 100. At Ping Identity, we're changing the way people and businesses think about cybersecurity, digital experiences, and identity and access management.

🎯 The Role

We are an experienced team of engineers who are hard working and easy to get along with. We have each other’s backs and are constantly sharing knowledge and pitching in whatever is needed to make sure our team and product are successful. We thrive on shared goals and shared success. We have mature yet lightweight processes around feature planning, defect tracking, and workload balance.

✅ Key Responsibilities

• Architect, build, and operate scalable ML platforms, tools, and services that enable data scientists and engineers to promote, evaluate, deploy, and monitor models in production
• Design and run the ML models’ feature store, ensuring offline/online consistency, feature reuse, lineage, and governance across training and serving paths.
• Own real-time ML in the critical path: streaming feature pipelines and low-latency, sub-second model serving in production
• Build efficient, automated data pipelines using Python, SQL, Airflow, and Spark to support ML training, inference, and analytics
• Drive MLOps end to end — CI/CD for models, containerized deployment on Docker/Kubernetes, monitoring, and continuous model lifecycle management
• Create tools, and utilities that reduce overhead and let data scientists focus on model development and research
• Architect and manage distributed big-data pipelines (Spark, Kafka, cloud-native data platforms), ensuring high availability and performance
• Work closely with Data Science, SRE, and Product teams to integrate ML capabilities into Ping's ecosystem
• See the big picture while coding the details: shape system architecture and technical direction, mentor engineers, and raise the engineering bar across teams

📌 Required Qualifications

• 6+ years of experience as an ML Engineer building ML platforms, data infrastructure, and large-scale distributed systems
• Expert-level programming skills in Python and SQL (Java is a plus)
• Deep hands-on experience with Spark or similar distributed computing frameworks
• Production experience with Airflow, MLflow, Kubernetes, and CI/CD pipelines
• Hands-on experience with offline and online feature stores (e.g., Redis) and real-time ML streaming data (e.g., Kafka and Flink) and low-latency model serving
• Experience with public cloud platforms (AWS preferred), including managed data and ML services (AWS SageMaker)
• Experience developing monitoring tools and utilities for data scientists, improving model training and deployment processes
• Ability to see the wide picture while implementing low-level technical details efficiently
• Great interpersonal communication skills, a strong team player who collaborates effectively across teams
• Strong problem-solving skills, thrives in fast-paced, agile environments

⭐ Desirable Experience

• Experience with modern lakehouse and data platform stacks, e.g., Apache Iceberg, dbt, OpenMetadata, and data governance/lineage
• Experience operating ML infrastructure across multi-account cloud environments with a self-service, low-ops philosophy
• Familiarity with deep learning, LLMs, or reinforcement learning, experience with PyTorch
• M.Sc. in the applied science field

🎁 Benefits

We believe in and facilitate a flexible, collaborative work environment. We’re growing quickly, but remain true to the innovative, can-do startup values that got us here. Most importantly, we keep hiring talented, smart, fun, and genuinely nice people because that’s who we want to succeed with every day.

Here are just a few of the things that make Ping special:

• A company culture that empowers you to do your best work.
• Employee Resource Groups that create a sense of belonging for everyone.
• Regular company and team bonding events.
• Competitive benefits and perks.
• Global volunteering and community initiatives

Our Benefits:

• Generous PTO & Holiday Schedule
• Parental Leave
• Progressive Healthcare Options
• Retirement Programs
• Opportunity for Education Reimbursement
• Commuter Offset (Specific locations)

🛂 Visa & Eligibility

Ping is the collective sum of all our individual experiences, backgrounds and influences and we pride ourselves in growing and learning together. We are committed to building an inclusive and diverse environment where everyone’s individuality is respected and everyone has an Identity. In recruiting for new colleagues, we welcome the unique contributions you can bring and encourage you to be your best self.

We are an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.