SailPoint is the leader in identity security for the cloud enterprise, providing unmatched visibility into the digital workforce. The Senior Machine Learning Engineer will shape, build, and scale AI-powered capabilities, leading complex ML initiatives from model design to deployment and continuous improvement.
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