Sr. Machine Learning Engineer

SailPoint is a leader in identity security for the cloud enterprise, delivering AI- and ML-powered solutions that help organizations secure access across their digital workforce. The company is seeking a Senior Machine Learning Engineer to design, build, deploy, and scale production-grade ML and AI systems that power customer insights, intelligent automation, and next-generation AI experiences. The role focuses on both classical machine learning and modern AI approaches such as foundation models, retrieval-augmented generation, and agentic workflows.

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
• • 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