Staff Machine Learning Engineer

SailPoint is the leader in identity security for the cloud enterprise, and they are seeking a Staff Machine Learning Engineer to shape, build, and scale their AI-powered capabilities. The role involves designing robust ML systems, collaborating with cross-functional teams, and leading complex ML initiatives to enhance SailPoint’s AI platform.

Responsibilities:

• 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
• Lead technical efforts to improve model accuracy, precision/recall trade-offs, and generalization across diverse regions and customer datasets
• Build and enhance ML infrastructure and pipelines for feature extraction, model training, evaluation, deployment, and monitoring
• Drive the technical strategy for reproducibility, model versioning, data lineage, and CI/CD automation in ML systems
• Collaborate with AI platform and DevOps teams to ensure reliable data access, observability, and efficient use of compute resources
• Set technical direction and best practices for ML engineering across the AI organization, influencing architecture and design standards
• Mentor and guide engineers in scalable ML design patterns, experimentation frameworks, and software craftsmanship
• Partner with product and engineering leaders to prioritize and deliver high-impact AI capabilities aligned with business goals
• Work cross-functionally with architecture, platform, and analytics teams to ensure AI components integrate seamlessly across SailPoint’s ecosystem
• Advance model lifecycle management, AI governance, and responsible AI practices to ensure quality, fairness, and transparency
• Communicate complex ML concepts into actionable insights and recommendations for technical and non-technical audiences
• Support day-to-day team operations in partnership with TPMs and managers, ensuring alignment and delivery across initiatives

Requirements:

• 8+ 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)
• Deep understanding of data modeling, feature engineering, and statistical analysis
• Expertise in data pipelines, ETL, and feature engineering using frameworks like Spark, Airflow, or dbt
• Solid knowledge of MLOps practices—including model monitoring, retraining, CI/CD, and experiment tracking
• Strong foundation in software engineering best practices: testing, modularization, code review, and observability
• Excellent communication and collaboration skills, with demonstrated experience leading cross-functional technical initiatives
• Experience with LLM-based solutions, embeddings, and retrieval-augmented generation (RAG)
• Familiarity with identity, security, or enterprise SaaS systems
• Experience designing AI platforms or reusable ML services that support multiple product lines
• Demonstrated ability to set technical direction, influence architectural decisions, and guide organizational strategy