*THIS IS A REMOTE ROLE BUT DOES REQUIRE AN IN PERSON INTERVIEWAbout the Role: 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 rol
e. You will design and build foundational ML systems and models, influence cross-team architecture, and set engineering standards that are adopted across multiple product lines. You will work at the intersection of modeling, ML infrastructure, and production systems, partnering closely with product, platform, and engineering leaders.
You are expected to operate at
organization scale: leading the most complex ML initiatives, mentoring engineers, and driving long-term technical strategy while still contributing directly to critical designs and implementations.
About the team: The AI team at SailPoint applies AI and domain expertise to create solutions that solve real problems in identity security. We believe the path to success is through meaningful customer outcomes, and we leverage classical ML, Graph ML, and recent innovations in Generative AI to bring our solutions to SailPoint's core product lines.
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, 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: - 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.
The Tech Stack (if applicable): - Core Programming: SQL, Python, Shell/Bash, Java or Rust
- Cloud Platform: AWS (SageMaker, Bedrock)
- Data: Snowflake, DBT, Kafka, Airflow, Feast
- CI/CD: Cloudbees, Jenkins
Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint.
As a part of the total compensation package, this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission, along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect SailPoint's differing products, industries, and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary, for US-based employees, will be in this range from (min-mid-max, USD):
$184,200 - $310,458.00
Base salaries for employees based in other locations are competitive for the employee's home location.
Benefits Overview
1. Health and wellness coverage: Medical, dental, and vision insurance
2. Disability coverage: Short-term and long-term disability
3. Life protection: Life insurance and Accidental Death & Dismemberment (AD&D)
4. Additional life coverage options: Supplemental life insurance for employees, spouses, and children
5. Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account
6. Financial security: 401(k) Savings and Investment Plan with company matching
7. Time off benefits: Flexible vacation policy
8. Holidays: 8 paid holidays annually
9. Sick leave
10. Parental support: Paid parental leave
11. Employee Assistance Program (EAP) and Care Counselors
12. Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options
13. Health Savings Account (HSA) with employer contribution
