Principal Machine Learning Engineer (AI)

TL;DR

Principal Machine Learning Engineer (AI): Design and build foundational ML systems and models for identity security platform with an accent on behavioral anomaly detection, semantic search, graph-based models, and LLM integrations. Focus on scaling production-grade ML pipelines, MLOps practices, and cross-team architecture for enterprise-scale reliability and performance.

United States Remote (Canada), requires in-person interview

$184,200 - $310,458 USD (US-based); competitive for other locations

Company

Leader in identity security for cloud enterprises, powering solutions with AI/ML for access management and visibility into digital workforces.

What you will do

• Define architectural vision for core ML systems, services, and platforms across products.
• Design, develop, and deploy production ML models including anomaly detection, semantic search, graph ML, and LLM-based solutions.
• Own end-to-end delivery of complex ML initiatives from data pipelines to monitoring and lifecycle management.
• Drive model improvements in quality, robustness, and performance on diverse datasets.
• Set ML engineering standards for experimentation, deployment, observability, and governance.
• Collaborate with product, platform, and engineering leaders to align AI roadmaps and influence architecture.

Requirements

• 12+ years in machine learning engineering or related field.
• Proven track record architecting large-scale production ML systems with business impact.
• Deep expertise in ML frameworks: PyTorch, TensorFlow, scikit-learn.
• Strong data modeling, feature engineering, statistics, and experimental design.
• Extensive MLOps: monitoring, CI/CD, experiment tracking, model lifecycle.
• Excellent communication to lead cross-functional stakeholders; BS/MS in CS or equivalent.

Nice to have

• Experience in cybersecurity, identity, or enterprise SaaS.
• Expertise in NLP, behavioral modeling, time series, or graph ML.
• Building ML at production scale in cloud-native environments.
• Designing reusable AI platforms supporting multiple products.

Culture & Benefits

• Health, dental, vision insurance; short/long-term disability, life insurance.
• 401(k) with matching, HSA with contribution, flexible spending accounts.
• Flexible vacation, sick leave, 8 paid holidays, paid parental leave.
• Employee Assistance Program, voluntary benefits including pet insurance.
• Potential corporate bonus, equity participation, competitive salary by location.

Hiring process

• In-person interview required for remote role.
• Architectural reviews, strategic discussions, technical contributions.