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Staff Machine Learning Engineer, Generative AI (Auth0)

Job Overview

Location

Toronto, Ontario, Canada

Job Type

Full-time

Category

Machine Learning Engineer

Date Posted

March 5, 2026

Full Job Description

đź“‹ Description

  • • As a Staff Machine Learning Engineer specializing in Generative AI at Okta, you will be at the vanguard of shaping and accelerating our company's strategic direction in artificial intelligence. This pivotal role involves deep engagement across the entire spectrum of model development, the underlying infrastructure that supports it, and the platform services that enable its widespread adoption.
  • • You will be instrumental in driving the design and implementation of production-ready AI/ML systems engineered for scale. This encompasses a broad range of applications, from sophisticated Large Language Model (LLM)-powered features that enhance user experiences to the creation of reusable platform components that empower other engineering teams across Okta to innovate and build upon our AI capabilities.
  • • A core responsibility will be to architect, design, and deploy robust Machine Learning and Generative AI systems. This includes ensuring seamless integration with a diverse array of platform services and establishing highly scalable LLMOps pipelines that are operational in production environments.
  • • You will lead critical initiatives focused on tuning, optimizing, and deploying agentic applications. The emphasis will be on achieving peak performance, unwavering reliability, and stringent security standards for these advanced AI systems.
  • • Collaboration is key in this role. You will partner closely with Product Management, Security, and Platform Engineering teams to conceptualize and develop AI-powered experiences that are not only groundbreaking and innovative but also inherently trustworthy and secure.
  • • You will contribute to the design of scalable, observable ML and Generative AI systems, integrating sophisticated retrieval, inference, and evaluation pipelines to ensure optimal performance and accuracy.
  • • A significant part of your work will involve developing and iterating on structured prompting techniques, advanced context retrieval mechanisms, and Retrieval-Augmented Generation (RAG) workflows. The goal is to systematically improve the accuracy, safety, and cost-efficiency of systems, particularly those leveraging models like Claude.
  • • You will be responsible for building and refining automated evaluation pipelines. These pipelines are crucial for rigorously measuring model quality, correctness, groundedness, and safety in real-world production settings.
  • • Implementing robust guardrails is paramount. This includes schema validation, structured output enforcement, and other critical measures to ensure that AI outputs are consistently reliable, auditable, and fully compliant with enterprise standards.
  • • You will play a key role in mentoring and coaching fellow engineers, fostering their professional growth and contributing to the collective expertise of the team and the broader engineering community at Okta.
  • • The role demands technical leadership, guiding architectural decisions, and making pragmatic choices that balance simplicity, flexibility, reliability, and performance to achieve optimal outcomes.
  • • You will leverage your expertise to design and implement components across various layers of the technology stack, utilizing modern tools and languages such as Python, and potentially exploring frameworks like LangGraph, DSPy, and MCP.
  • • You will contribute to the development of intelligent security features, enhancing the overall security posture of Okta's identity platform through AI-driven insights and automation.
  • • The opportunity exists to work on cutting-edge AI agent frameworks, contributing to the development of sophisticated AI agents that can perform complex tasks and interact seamlessly with users and systems.
  • • You will be at the forefront of developing the best developer experience around authentication for generative AI and AI agents, ensuring that integrating these powerful technologies is secure, straightforward, and efficient.
  • • By joining the AI Frameworks and Services team, you will be directly contributing to the foundational frameworks and essential services that empower engineering teams across Okta to integrate state-of-the-art AI capabilities into our products, fundamentally transforming how our users interact with them and driving significant business value.
  • • This role offers a unique chance to work on generative AI-powered chat experiences designed to provide instant, intelligent product support, showcasing the practical application of AI in customer-facing scenarios.
  • • You will be a key player in bringing the transformative power of AI to life within Okta, making a tangible impact on product innovation and user satisfaction.
  • • The team's mission is to build the intelligent features that power seamless product experiences, and as a Staff ML Engineer, you will be central to achieving this vision.
  • • You will collaborate closely with the broader Machine Learning team and various product teams to ensure the secure, efficient, and impactful delivery of AI-enhanced features that provide real, measurable value to our users.
  • • This position is ideal for a seasoned professional eager to make a significant impact in the rapidly evolving field of Generative AI within a leading identity management company.

Skills & Technologies

Python
TypeScript
Go
FastAPI
AWS
Senior
Remote

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About Okta, Inc.

Okta provides cloud-based identity and access management software that enables organizations to securely connect employees, partners, and customers to the right technologies. Its platform offers single sign-on, multi-factor authentication, lifecycle management, API access control, and analytics to manage user identities across applications, devices, and networks. The company serves enterprises, government agencies, and small to medium-sized businesses, helping them improve security, compliance, and user experience while reducing IT complexity and support costs.

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