Senior Machine Learning Engineer

7 hours ago

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SailPoint

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Cybersecurity • Enterprise • SaaS

SailPoint is a leader in identity security solutions, providing an intelligent and autonomous platform designed to meet the evolving security needs of modern enterprises. Their products, including IdentityIQ and Identity Security Cloud, offer a unified and comprehensive approach to managing and securing enterprise identities. SailPoint helps organizations mitigate cyber risks, improve IT efficiency, and maintain compliance through advanced capabilities such as cloud infrastructure entitlement management, non-employee risk management, and data access security. By integrating AI and machine learning, SailPoint enables organizations to streamline identity processes, enhance security measures, and accelerate onboarding. They serve multiple industries, including education, financial services, government, and healthcare, by offering tailored identity governance and administration solutions.

1001 - 5000 employees

Founded 2005

🔒 Cybersecurity

🏢 Enterprise

☁️ SaaS

📋 Description

• 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.

🏖️ Benefits

• Health and wellness coverage: Medical, dental, and vision insurance • Disability coverage: Short-term and long-term disability • Life protection: Life insurance and Accidental Death & Dismemberment (AD&D) • Additional life coverage options: Supplemental life insurance for employees, spouses, and children • Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account • Financial security: 401(k) Savings and Investment Plan with company matching • Time off benefits: Flexible vacation policy • Holidays: 8 paid holidays annually • Sick leave • Parental support: Paid parental leave • Employee Assistance Program (EAP) and Care Counselors • Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options • Health Savings Account (HSA) with employer contribution