Staff Machine Learning Engineer (Remote)

Job title: Staff Machine Learning Engineer (Remote)

About the Role As a Staff Machine Learning Engineer, you will play a critical role in shaping, building, and scaling SailPoint’s AI-powered capabilities. You’ll work at the intersection of AI innovation, software engineering, and platform architecture—designing robust, production-grade ML systems that deliver customer insights and intelligent automation across our identity platform. As a senior technical leader, you’ll partner closely with engineering, AI, and product teams to drive innovation, define our ML strategy, and mentor others in applying best practices for scalable, responsible AI.

What You'll Do

• 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.

What We're Looking For

• 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.

Nice to Have

• Preferred: 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.

Compensation & Benefits

• Salary and benefits not disclosed.