Senior Machine Learning Engineer (REMOTE)

SailPoint is the leader in identity security for the cloud enterprise, providing unmatched visibility and access management for digital workforces. The Senior Machine Learning Engineer will be responsible for designing and implementing machine learning models to enhance SailPoint’s AI capabilities, leading complex ML initiatives from inception to deployment.

Responsibilities:

• Design, experiment with, and implement ML models to solve complex identity security challenges
• Take ownership of research and prototyping efforts in areas like embeddings, representation learning, and similarity measurement
• Translate AI research and prototypes into practical, effective, and production-ready systems
• Drive improvements in model accuracy, precision/recall, and generalization for your projects
• Implement and advocate for best practices in ML engineering, testing, and architecture
• Communicate complex ML concepts and project updates to technical and non-technical stakeholders
• Partner with product managers to scope and deliver high-impact AI capabilities
• Work cross-functionally with platform and analytics teams to ensure your components integrate seamlessly into SailPoint’s ecosystem
• Contribute to our model lifecycle management, AI governance, and responsible AI practices

Requirements:

• 5+ years of professional experience in a technical field with a focus on machine learning
• Proven experience applying modeling techniques such as anomaly detection, semantic search, embeddings, or similarity measurement to real-world applications
• Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Solid understanding of data modeling, feature engineering, and statistical analysis
• Excellent communication skills and the ability to collaborate effectively in a cross-functional team
• Strong foundation in software engineering best practices: testing, modularization, code review, and observability
• Good knowledge of MLOps practices—including model monitoring, retraining, and CI/CD
• Experience in cybersecurity, identity, or enterprise SaaS systems
• Expertise in at least one of our core modeling areas: NLP, Behavioral Modeling, or Graph ML
• Experience owning the technical design and delivery of complex ML components or features
• Hands-on experience building and deploying ML models in a cloud-native environment