About the team:

The AI Group at SailPoint is seeking a Senior Machine Learning Engineer to help shape the future of AI-driven identity governance. In this role, you will contribute to the design and development of SailPoint’s AI Platform and leverage it to deliver innovative machine learning and generative AI solutions that power our core products. If you are passionate about creating scalable, impactful AI/ML systems and enjoy working at the intersection of cutting-edge research and product development, we would love to connect with you.

This position is Remote or Hybrid.

Responsibilities

• Design, build, and maintain a production-grade machine learning platform
• Develop and deploy ML models using the platform
• Extend platform capabilities to support Generative AI workloads
• Establish repeatable patterns that ensure reliable model deployments
• Collaborate with ML Engineers, Software Engineers, and Data Scientists to deliver production-ready AI features
• Ensure models are deployed, monitored, and tracked with clear, actionable dashboards.
• Deliver efficient, maintainable, and robust microservices to support AI features.
• Partner with application teams to build secure, scalable, and SLA-compliant solutions
• Build batch and streaming data pipelines to populate the feature store.
• Must be willing to be part of an on-call rotation.

Requirements

• Minimum of 5+ years of experience working as a Machine Learning Engineer or Data Scientist.
• Experience deploying ML models into production.
• A self-starter who can engage on ambiguous assignments and provide thought leadership.
• Strong verbal and written communication skills, with the ability to translate complex concepts into easy-to-understand language for product and business stakeholders.
• Understanding of common ML algorithms and techniques (e.g., clustering, classification, regression).
• Strong command of MLOps best practices and existing frameworks.
• Experience with feature stores such as Feast.
• Experience implementing RESTful APIs for an API-first application architecture.
• Experience building microservices and knowledge of common microservice design patterns.
• Experience with Docker or other container technologies.
• (Preferred) Experience with AWS, Amazon SageMaker, and Amazon Bedrock.
• (Preferred) Experience building services using GenAI technology.
• (Preferred) Experience with Amazon Bedrock or other services for building GenAI applications.

Roadmap To Success

First 90 Days

• Get onboarded to SailPoint’s AI platform architecture and tools
• Contribute to the codebase: small PRs on microservices or model pipelines.
• Deploy a simple ML model or change to an existing model through the platform.
• Define model monitoring and observability standards for a new model.
• Shadow and eventually join the on-call rotation.

6 Months

• Work on deployment of an end-to-end ML use case into production.
• Deliver efficient, maintainable, and robust code.
• Fully participate in on-call rotation and drive process improvements.
• Identify and implement improvements to the broader AI Platform.

1 Year

• Collaborate with multiple teams to ship high-impact ML/GenAI features.
• Help shape SailPoint’s broader AI Platform strategy to drive measurable improvements in velocity and quality of model delivery.
• Contribute to evaluation and adoption of new tooling to enhance our platform.
• Mentor junior engineers and AI Platform users.

Benefits and Compensation

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):

$119,400 - $170,500 - $221,700

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