Staff Machine Learning Engineer (Remote)

About SailPoint:

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 Staff 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.

As a senior technical leader youll partner closely with engineering AI and product teams to drive innovation define our ML strategy and mentor others in applying best practices for scalable responsible AI.

This is both a hands-on and strategic role. 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.

• Lead technical efforts to improve model accuracy precision/recall trade-offs and generalization across diverse regions and customer datasets.

• Build and enhance ML infrastructure and pipelines for feature extraction model training evaluation deployment and monitoring.

• Drive the technical strategy for reproducibility model versioning data lineage and CI/CD automation in ML systems.

• Collaborate with AI platform and DevOps teams to ensure reliable data access observability and efficient use of compute resources.

• Set technical direction and best practices for ML engineering across the AI organization influencing architecture and design standards.

• Mentor and guide engineers in scalable ML design patterns experimentation frameworks and software craftsmanship.

• Partner with product and engineering leaders to prioritize and deliver high-impact AI capabilities aligned with business goals.

• Work cross-functionally with architecture platform and analytics teams to ensure AI components integrate seamlessly across SailPoints ecosystem.

• Advance model lifecycle management AI governance and responsible AI practices to ensure quality fairness and transparency.

• Communicate complex ML concepts into actionable insights and recommendations for technical and non-technical audiences.

• Support day-to-day team operations in partnership with TPMs and managers ensuring alignment and delivery across initiatives.

Requirements:

• 8 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).

• Deep understanding of data modeling feature engineering and statistical analysis.

• Expertise in data pipelines ETL and feature engineering using frameworks like Spark Airflow or dbt.

• Solid knowledge of MLOps practicesincluding model monitoring retraining CI/CD and experiment tracking.

• Strong foundation in software engineering best practices: testing modularization code review and observability.

• Excellent communication and collaboration skills with demonstrated experience leading cross-functional technical initiatives.

Preferred

• Experience with LLM-based solutions embeddings and retrieval-augmented generation (RAG).

• Familiarity with identity security or enterprise SaaS systems.

• Experience designing AI platforms or reusable ML services that support multiple product lines.

• Demonstrated ability to set technical direction influence architectural decisions and guide organizational strategy.

Roadmap for success-

30 days:

• Gain deep understanding of SailPoints AI vision architecture and active ML initiatives.

• Familiarize with existing data pipelines environments and model deployment frameworks.

• Build relationships with key stakeholders across AI platform DevOps and product teams.

• Conduct hands-on review of current ML models data flows and monitoring systems to identify immediate optimization or reliability gaps.

• Begin contributing to small improvements or code reviews to gain familiarity with production practices.

90 days:

• Lead at least one end-to-end ML enhancement or pilot.

• Establish and document best practices for reproducibility observability and CI/CD for ML systems.

• Mentor junior engineers and support team-wide code quality and experimentation standards.

• Present a roadmap or proposal for scaling AI components or addressing key technical debt areas.

6 months:

• Deliver measurable impact on model performance reliability or scalability for at least one core AI product.

• Lead design and implementation of a shared ML service or reusable component (e.g. feature store inference service or monitoring framework).

• Be recognized as a technical go-to for complex ML engineering and architecture decisions.

1 year:

• Establish SailPoints ML engineering foundation as robust scalable and production-ready across multiple AI initiatives.

• Drive one or more flagship AI capabilities from prototype to production with demonstrated business or customer impact.

• Mentor and elevate other engineers fostering a culture of technical excellence and continuous learning.

• Influence long-term AI platform architecture and strategic investment areas as part of the broader AI leadership group.

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.