Senior Machine Learning Engineer (REMOTE)

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 jobno 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 timematching the scale velocity and changing needs of todays cloud-oriented modern enterprise.

About the Role

As a Senior Machine Learning Engineer you will play a critical role in shaping building and scaling SailPoints AI-powered capabilities. Youll work at the intersection of AI innovation software engineering and platform architecturedesigning robust production-grade ML systems that deliver customer insights and intelligent automation across our identity platform.

You will lead complex end-to-end ML initiativesfrom model design and experimentation to deployment monitoring and continuous improvementwhile advancing the evolution of SailPoints 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 SailPoints 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 SailPoints business goals.

• Work cross-functionally with architecture platform and analytics teams to integrate ML systems seamlessly into SailPoints 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 practicesmodel 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 SailPoints 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 products 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 SailPoints 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):

Base salaries for employees based in other locations are competitive for the employees 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 or mail to 11120 Four Points Dr Suite 100 Austin TX 78726 to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.