The Machine Learning Operations Team at SailPoint builds and maintains our ML Platform, the infrastructure used to deploy and monitor the thousands (and growing fast!) of machine learning models in production powering some of our most innovative and compelling product features. The models span a variety of ML disciplines, including Generative AI and LLMs, Recommender Systems, Graph ML, and traditional supervised and unsupervised learning. This team sits at the center of our ML group, working closely with our data scientists and product engineering teams to bring AI features to life with the scalability and reliability required of an enterprise product.

If you have proven experience with the deployment and operations side of machine learning and a passion for building high-quality and intuitive AI products, we’d love to talk. This is a high impact role. The team, the scale of our model deployments, and the scope of our mandate are all increasing quickly, and we’re looking for someone who is eager to be a core part in growing our team and establishing the ML culture at SailPoint.

This position is remote or hybrid based in Austin, TX.

Responsibilities:

• Manage a team of machine learning engineers tasked with building our ML operations infrastructure for deploying and monitoring models.
• Design processes to govern model deployments and help the team operate effectively.
• Prioritize the team’s work to align with our broader AI roadmap and maximize impact.
• Collaborate closely with our data science team(s) to guide the promotion of features from R&D to product, with an eye towards testability, scalability, and cost efficiency.
• Establish processes to improve triage and root cause analysis of production ML issues.
• Coach and develop your direct reports to effectively scale our organization.
   

Qualifications:

• 8+ years engineering experience
• 1-3 years of people management experience with engineers or data scientists
• Thorough understanding of end-to-end AI model development, with particular emphasis on model testing, deployment, and production monitoring.
• Proven experience building and deploying machine learning models into production.
• Experience with offline (batch) and online (real-time/streaming) feature stores.
• Familiarity with common ML models and how to integrate with them.
• Comfort communicating with data science, engineering, and DevOps teams.
• Experience with cloud computing workflows + services for AI/ML (bonus if it’s AWS).
• Strong technical & problem-solving skills: ability to execute on ambiguous tasks.
• Fantastic communication and interpersonal skills.
   

Bonus:

• B.S. in Computer Science or related field
• Experience with LLMs and associated open source and cloud technologies.
• Experience with large-scale distributed computing technologies such as Apache Spark.

SailPoint is an equal opportunity employer and we welcome everyone to our team.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.