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SailPoint

Staff Machine Learning Engineer (REMOTE)

Job Posted 3 Days Ago Posted 3 Days Ago
Remote or Hybrid
Hiring Remotely in United States
141K-262K Annually
Senior level
Remote or Hybrid
Hiring Remotely in United States
141K-262K Annually
Senior level
The Staff Machine Learning Engineer will build and manage production-grade ML systems, focusing on scalable model development, deployment, and governance within the AI Platform team.
The summary above was generated by AI

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 team:

The AI Platform team at SailPoint builds and operates the core infrastructure that we use to deploy and monitor our ML solutions across our products. We enable scalable model development, deployment, monitoring, and governance, supporting both traditional ML and cutting-edge GenAI use cases. Our work bridges data science and engineering, providing robust tools, services, and best practices to accelerate the delivery and impact of AI features.We are looking for a Staff Machine Learning Engineer to join the team.

Requirements:

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

  • 5 to 8 years of experience

  • Demonstrated experience building and managing production-grade ML systems on could platforms (preferably AWS).

  • Strong understanding of the ML lifecycle, including development, data/feature engineering, versioning, monitoring, and debugging in production environments.

  • Excellent communication skills, with the ability to clearly convey complex technical concepts to both technical and non-technical audiences.

  • Working knowledge of common ML algorithms and technologies.

  • A bias for action and ability to navigate ambiguity.

Tech Stack:

  • Core Programming Languages: Python, Go, Java

  • Cloud Platform: AWS (SageMaker, Bedrock) preferred

  • GenAI Frameworks/Tools: Any

  • Data: Snowflake, Kafka, Airflow

  • CI/CD frameworks such as Jenkins or Cloudbees

  • Observability frameworks such as Prometheus / Grafana

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

  • Lead the 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 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):

$141,300 - $201,800 - $262,300

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 hr@sailpoint.com or mail to 11120 Four Points Dr, Suite 100, Austin, TX 78726, to discuss reasonable accommodations.

Top Skills

Airflow
AWS
Cloudbees
Go
Grafana
Java
Jenkins
Kafka
Prometheus
Python
Snowflake

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