Senior Machine Learning Engineer (REMOTE)

Role overview

Senior Machine Learning Engineer (Remote)

You will shape, build, and scale SailPoint’s AI-powered capabilities by designing production-grade ML systems that provide customer insights and intelligent automation across the identity platform.

Responsibilities

• Design, experiment with, and implement ML models for complex identity security challenges.
• Lead end-to-end ML initiatives: model design, experimentation, deployment, monitoring, and continuous improvement.
• Own research and prototyping in areas such as:
  • Embeddings
  • Representation learning
  • Similarity measurement
• Translate AI research/prototypes into production-ready systems.
• Improve model performance (e.g., accuracy, precision/recall, and generalization).
• Apply ML engineering best practices (testing, architecture, and development standards).
• Communicate complex ML concepts and progress 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 seamless integration.
• Contribute to model lifecycle management, AI governance, and responsible AI practices.

Requirements

• 5+ years of professional experience in a technical field focused on machine learning.
• Experience applying modeling techniques such as:
  • Anomaly detection
  • Semantic search
  • Embeddings / similarity measurement
• Strong Python programming skills and ML framework proficiency in one or more of:
  • PyTorch, TensorFlow, scikit-learn
• Solid understanding of data modeling, feature engineering, and statistical analysis.
• Strong software engineering fundamentals (testing, modularization, code review, observability).
• Knowledge of MLOps practices (model monitoring, retraining, CI/CD).
• Excellent communication and cross-functional collaboration skills.

Preferred qualifications

• Experience in cybersecurity, identity, or enterprise SaaS.
• Expertise in at least one: NLP, Behavioral Modeling, or Graph ML.
• Experience owning technical design and delivery of complex ML components/features.
• Hands-on experience deploying ML models in cloud-native environments.