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. We are looking for a strong machine learning practitioner with deep machine learning expertise and hands-on experience developing and deploying both classical machine learning solutions and agentic AI systems.

You'll work at the intersection of AI innovation and software engineering, designing production-grade ML and AI systems that deliver customer insights, intelligent automation, and next-generation AI experiences across our identity platform.

The ideal candidate combines strong machine learning fundamentals with hands-on experience applying modern AI techniques, including foundation models, retrieval-augmented generation (RAG), and agentic workflows to solve real-world customer problems.

You will lead complex, end-to-end AI initiatives, from model design and experimentation to deployment, monitoring, and continuous improvement.

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, develop, and deploy machine learning and AI-powered solutions to solve complex identity security challenges.
• Own research, prototyping, and implementation efforts across both classical ML capabilities (e.g., semantic search, behavioral modeling, embeddings) and agentic AI systems leveraging foundation models, RAG, and orchestration frameworks.
• Evaluate and apply modern AI techniques, including foundation models, agents, fine-tuning, and model evaluation frameworks, to create new product capabilities.
• Translate AI research and prototypes into practical, effective, and production-ready systems.
• Drive improvements in model quality, accuracy, reliability, and scalability for the solutions you own.
• Implement and advocate for best practices in ML engineering, testing, observability, and architecture.
• Communicate complex AI and ML concepts to both technical and non-technical stakeholders.
• Partner with product managers and engineering teams to scope and deliver high-impact AI capabilities.
• Work cross-functionally with platform and analytics teams to ensure solutions integrate seamlessly into SailPoint's ecosystem.
• Contribute to model lifecycle management, AI governance, and responsible AI practices.

Requirements:

• 5+ years of professional experience in machine learning, AI, or a related technical field.
• Deep machine learning expertise with experience building and deploying production ML systems.
• Experience building AI-powered applications using LLMs, retrieval-augmented generation (RAG), prompt engineering, agent frameworks, or related technologies.
• Proven experience applying techniques such as anomaly detection, semantic search, embeddings, similarity measurement, classification, or ranking to real-world problems.
• Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Strong understanding of data modeling, feature engineering, statistical analysis, experimentation, and model evaluation.
• Proven experience building and operating ML systems in production environments.
• Strong software engineering fundamentals, including testing, modularization, code reviews, observability, and operational excellence.
• Knowledge of MLOps practices, including model monitoring, experiment tracking, retraining, and CI/CD.
• Excellent communication and collaboration skills, with experience working across cross-functional teams.
• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Preferred

• Experience in cybersecurity, identity, or enterprise SaaS systems.
• Deep expertise in one or more of the following areas: NLP, Behavioral Modeling, Time Series, Graph ML, Search, or Recommendation Systems.
• Experience owning the technical design and delivery of complex ML or AI capabilities.
• Experience designing or implementing AI agents, agentic workflows, or autonomous AI systems.
• Hands-on experience building and deploying ML and AI applications in cloud-native environments.
• Demonstrated track record of delivering measurable business impact through AI and machine learning solutions.

Roadmap for success-

30 days:

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

90 days:

• Contribute to at least one end-to-end ML or AI initiative, supporting improvements in performance, reliability, or scalability.
• Develop or evaluate an AI-powered workflow, agent, or prototype using existing platform capabilities.
• Participate in model evaluation and analysis, identifying opportunities for feature, data, and architecture improvements.
• Collaborate with stakeholders to identify opportunities to improve scalability, reduce technical debt, or expand AI capabilities.

6 months:

• Deliver a significant improvement to a core AI product's performance, scalability, reliability, or customer impact.
• Contribute to the design or enhancement of reusable ML and AI platform components.
• Drive improvements to model evaluation, deployment processes, monitoring, and operational reliability.
• Be recognized as a key contributor and technical resource for ML and AI engineering within the team.

1 year:

• Deliver one or more high-impact AI solutions from concept to production.
• Help establish a robust and scalable foundation for both traditional ML and agentic AI capabilities.
• Contribute to AI architecture and technical roadmap discussions through successful delivery and technical expertise.
• Drive adoption of emerging AI technologies, including foundation models, agents, and orchestration frameworks where they provide meaningful customer value.
• Mentor and elevate peers through collaboration, technical leadership, 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, Iceberg, Feast
• 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-max, USD):
$124,900 - $210,512.00
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