AI Scientist

Saviynt's AI-powered identity platform manages and governs human and non-human access to all of an organization's applications, data, and business processes. Customers trust Saviynt to safeguard their digital assets, drive operational efficiency, and reduce compliance costs. Built for the AI age, Saviynt is today helping organizations safely accelerate their deployment and usage of AI. Saviynt is recognized as the leader in identity security, with solutions that protect and empower the world’s leading brands, Fortune 500 companies and government institutions. For more information, please visit www.saviynt.com.

In this role, you will build a risk identity model for AI agents to determine if their activities are incongruent with their assumed identities. This will help secure customers who are looking for identity security coverage in the AI era.

The AI Research Team builds AI in Saviynt products, we create Machine Learning and Language Model solutions and test their accuracy, we work with Engineering to get those models into production so that they can protect our customers. We are at the forefront of Saviynt’s AI revolution, we serve as examples and act as consultants to uplevel AI efforts across the company.

WHAT YOU WILL BE DOING

• Join the AI Research Team as we build AI for Identity Security
• Collaborate with product managers and other engineers to build amazing products
• Come up with novel solutions to hard problems
• Design, implement, and test software components or models
• Get patents for your great ideas
• Communicate results and insights to technical and non-technical audiences

WHAT YOU BRING

• Graduating in 2026 with a Masters or PhD in Computer Science, Data Science, Engineering, or a related field
• Strong foundation in Python, Java, or similar programming languages
• Familiarity with data structures, algorithms, and software development principles
• Experience in applied AI or machine learning
• Excellent problem-solving skills, curiosity, and eagerness to learn
• Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Familiarity with AWS, Azure, GCP, or container technologies like Docker/Kubernetes