Principal Machine Learning Engineer

SailPoint

Principal Machine Learning Engineer driving ML capabilities and architectural vision for identity security solutions at SailPoint. Collaborating with engineering leaders in a remote environment.

Posted 4/29/2026full-timeTexas • 🇺🇸 United StatesLead💰 $184,200 - $310,458 per yearWebsite

Tech Stack

Tools & technologies

PyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Define and lead the architectural vision for core ML systems, services, and platforms used across SailPoint products.
Design, develop, and deploy production-grade ML models including behavioral and anomaly detection, semantic search and embeddings, similarity-based systems, graph-based models, and LLM-based or hybrid solutions where appropriate.
Translate research, experimentation, and prototypes into scalable, maintainable, and reusable production systems.
Own end-to-end technical design and delivery for complex ML initiatives, from data pipelines and feature engineering through deployment, monitoring, and lifecycle management.
Drive continuous improvements in model quality, robustness, generalization, and performance across diverse enterprise datasets.
Set and evolve ML engineering standards spanning experimentation rigor, evaluation, deployment, observability, and governance.
Partner with platform, data, and DevOps teams to ensure reliable data access, cost-efficient compute usage, and high system availability.
Collaborate closely with product and engineering leaders to define AI roadmaps, prioritize work, and deliver high-impact customer capabilities.
Influence architectural decisions across teams to ensure ML solutions are reusable, scalable, and aligned with long-term platform strategy.
Communicate complex ML concepts and technical decisions clearly to technical and non-technical stakeholders, including senior leadership.
Mentor engineers on ML system design, software craftsmanship, and best practices for building production AI systems.
Act as a technical authority for the most challenging ML and AI platform problems.

Requirements

What you’ll need

12+ years of experience in machine learning engineering, software engineering, or a related technical field.
Proven track record of architecting and delivering large-scale, production ML systems with meaningful business impact.
Deep hands-on expertise with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
Strong foundation in data modeling, feature engineering, statistics, and experimental design.
Extensive experience with MLOps practices, including monitoring, CI/CD, experiment tracking, and model lifecycle management.
Excellent communication and collaboration skills, with demonstrated ability to lead and influence cross-functional, senior-level stakeholders.
BS or MS in Computer Science or a related field, or equivalent professional experience.

Benefits

Comp & perks

Health and wellness coverage: Medical, dental, and vision insurance
Disability coverage: Short-term and long-term disability
Life protection: Life insurance and Accidental Death & Dismemberment (AD&D)
Additional life coverage options: Supplemental life insurance for employees, spouses, and children
Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account
Financial security: 401(k) Savings and Investment Plan with company matching
Time off benefits: Flexible vacation policy
Holidays: 8 paid holidays annually
Sick leave
Parental support: Paid parental leave
Employee Assistance Program (EAP) and Care Counselors
Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options
Health Savings Account (HSA) with employer contribution

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learning engineeringsoftware engineeringarchitecting ML systemsproduction ML modelsdata pipelinesfeature engineeringMLOps practicesdata modelingstatisticsexperimental design

Soft Skills

communication skillscollaboration skillsleadershipinfluencementoring

Certifications

BS in Computer ScienceMS in Computer Science