[Hiring] Principal Machine Learning Engineer @SailPoint

Role Description

As a Principal Machine Learning Engineer on the Core AI / ML team, you will be a senior technical leader responsible for shaping, scaling, and operationalizing ML capabilities that power SailPoint’s product offerings. This is a hands-on, end-to-end technical leadership role.

• Design and build foundational ML systems and models.
• Influence cross-team architecture and set engineering standards adopted across multiple product lines.
• Work at the intersection of modeling, ML infrastructure, and production systems.
• Partner closely with product, platform, and engineering leaders.
• Lead the most complex ML initiatives, mentor engineers, and drive long-term technical strategy.
• Contribute directly to critical designs and implementations.

Responsibilities

• 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
  • LLM-based or hybrid solutions
• 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.

Qualifications

• 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.

Preferred

• Experience in cybersecurity, identity, or enterprise SaaS systems.
• Deep expertise and a strong track record in at least one of our core modeling areas: NLP, Behavioral Modeling, Time Series or Graph ML.
• Proven track record of building and deploying ML models at production scale (cloud-native environments preferred).
• Demonstrated ability to set technical direction, influence architectural decisions, and guide organizational strategy.
• Experience designing reusable AI platforms or ML services that support multiple product lines.

Roadmap for Success

• 30 days:
  • Develop a deep architectural understanding of SailPoint's identity platform, AI/ML infrastructure, and active initiatives.
  • Identify key strategic opportunities and technical challenges for integrating Core AI/ML capabilities.
  • Establish yourself as a technical leader within the team and build key relationships with stakeholders across engineering, AI, and product.
  • Begin contributing to architectural reviews and strategic discussions to gain familiarity with production practices.
• 90 days:
  • Define and champion the architectural vision and roadmap for a major Core AI/ML initiative.
  • Lead the design and initial implementation of foundational components for that initiative.
  • Establish and evangelize best practices for ML engineering, MLOps, and responsible AI tailored to the identity domain.
• 6 months:
  • Deliver significant, measurable impact on the performance, scalability, or capabilities of a core identity product through the integration of AI/ML.
  • Be recognized across the organization as the go-to technical expert for Core AI/ML and its application to identity security.
  • Drive key architectural decisions that shape the future of the AI platform and influence the broader engineering organization.
• 1 year:
  • Solidify the technical foundation for Core AI/ML at SailPoint, ensuring it is robust, scalable, and a key driver of innovation.
  • Lead one or more flagship AI capabilities from strategic conception to successful production deployment, delivering transformative value to our customers.
  • Actively mentor and grow the next generation of technical leaders within the AI organization.

Benefits

• 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