Senior Machine Learning Engineer (remote) - Remote Eligible

Senior Machine Learning Engineer

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce and ensuring that workers have the right access to do their job—no more and no less.

Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time—matching the scale, velocity, and changing needs of today's cloud-oriented, modern enterprise.

About the Role

As a Senior Machine Learning Engineer, you will play a critical role in shaping, building, and scaling SailPoint's AI-powered capabilities. You'll work at the intersection of AI innovation, software engineering, and platform architecture—designing robust, production-grade ML systems that deliver customer insights and intelligent automation across our identity platform.

You will lead complex, end-to-end ML initiatives—from model design and experimentation to deployment, monitoring, and continuous improvement—while advancing the evolution of SailPoint's AI platform, data pipelines, and model governance standards.

About the Team

The AI team at SailPoint applies AI and domain expertise to create AI solutions that solve real problems in identity security. We believe the path to success is through meaningful customer outcomes, and we leverage classical ML as well as recent innovations in Generative AI and Graph ML to bring our solutions to SailPoint's core product lines.

Responsibilities

• Design, implement, and optimize ML models (supervised, unsupervised, and LLM-based) that power both customer-facing and internal product capabilities.
• Translate AI research and experimental prototypes into scalable, maintainable production systems.
• Drive technical execution to improve model accuracy, precision/recall balance, and generalization across customer datasets and regions.
• Contribute to defining technical best practices for ML engineering across the AI team and participate in architecture and design discussions.
• Partner with product and engineering teams to scope, prioritize, and deliver impactful AI features aligned with SailPoint's business goals.
• Work cross-functionally with architecture, platform, and analytics teams to integrate ML systems seamlessly into SailPoint's ecosystem.
• Champion responsible AI principles and support ongoing improvements in model governance, explainability, and fairness.
• Communicate technical insights clearly, enabling shared understanding across technical and non-technical stakeholders.

Requirements

• 5+ years of professional experience in machine learning engineering, software development, or a related technical field.
• Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Proven track record of building and deploying ML models at production scale (cloud-native environments preferred).
• Solid understanding of data modeling, feature engineering, and statistical analysis.
• Hands-on experience with data pipelines and ETL frameworks such as Spark, Airflow, or dbt.
• Working knowledge of MLOps practices—model monitoring, retraining, CI/CD, and experiment tracking.
• Strong grasp of software engineering fundamentals: testing, modularization, code review, and observability.
• Excellent communication and collaboration skills; proven ability to work effectively across cross-functional teams.

Preferred

• Exposure to LLM-based solutions, embeddings, or retrieval-augmented generation (RAG).
• Understanding of identity, security, or enterprise SaaS systems.
• Experience contributing to or extending shared ML infrastructure or platform components.

Roadmap for Success

30 days:

• Build a strong understanding of SailPoint's AI vision, architecture, and current ML initiatives.
• Learn existing data pipelines, environments, and model deployment frameworks.
• Establish working relationships with key partners across AI, platform, DevOps, and product teams.
• Review current ML models, data flows, and monitoring systems to identify optimization opportunities.
• Contribute to initial improvements or bug fixes to gain familiarity with production workflows.

90 days:

• Contribute to at least one end-to-end ML initiative or pilot, supporting improvements in performance, reliability, or scalability.
• Participate in model evaluation and analysis, helping to identify gaps, edge cases, or areas for feature and data improvements to support robust production performance.
• Collaborate with stakeholders to identify opportunities to improve scalability, reduce technical debt, or enhance ML capabilities.

6 months:

• Deliver a significant improvement to a core AI product's performance, scalability, or reliability.
• Contribute to the design or enhancement of a reusable ML component (e.g., inference service, feature store, or monitoring framework).
• Be recognized as a key contributor and technical resource for ML engineering within the AI team.

1 year:

• Help establish a robust, scalable ML foundation across multiple AI initiatives.
• Deliver one or more high-impact ML solutions from concept to production.
• Mentor and elevate peers through collaboration and knowledge sharing.

The Tech Stack (if applicable):

• Core Programming: SQL, Python, Shell/Bash, Go
• Cloud Platform: AWS (SageMaker, Bedrock)
• Data: Snowflake, DBT, Kafka, Airflow, Feast
• Visualization: Tableau, Qlik
• 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): $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

SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable law.

Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact applicationassistance@sailpoint.com or mail to 11120 Four Points Dr, Suite 100, Austin, TX