Staff Machine Learning Engineer, AIFS (Auth0)

Get to know Okta

Okta is The World’s Identity Company. We free everyone to safely use any technology, anywhere, on any device or app. Our flexible and neutral products, Okta Platform and Auth0 Platform, provide secure access, authentication, and automation, placing identity at the core of business security and growth.At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box - we’re looking for lifelong learners and people who can make us better with their unique experiences.Join our team! We’re building a world where Identity belongs to you.

The Team:

Have you ever considered what powers the intelligent features behind seamless product experiences? The AI Frameworks and Services team is at the forefront of enabling AI-driven innovation across our organization. We build the foundational frameworks and essential services that empower engineering teams to integrate cutting-edge AI capabilities into our products, transforming how our users interact with them. From crafting intuitive generative AI-powered chat experiences that provide instant product support, to developing the best developer experience around authentication for generative AI and AI agents, as well as implementing intelligent security features, our team is instrumental in bringing the transformative power of AI to life. We collaborate closely with the Machine Learning team and various product teams to ensure the seamless and secure delivery of AI-enhanced features that provide real value to our users.

The Opportunity:

As a Staff Machine Learning Engineer on the Generative AI team, you will help shape and accelerate our Generative AI strategy by contributing across the stack of model development, infrastructure, and platform services. You’ll drive design and implementation of production-ready AI/ML systems at scale—ranging from LLM-powered features to reusable platform components that other teams across Okta can build on.

You will have the opportunity to:

• Design and implement scalable infrastructure and platform services for large-scale Generative AI use cases.
• Drive technical decision making while striving to hit the right balance between factors such as simplicity, flexibility, reliability, and performance.
• Architect, design, and deploy robust Machine Learning & GenAI systems, ensuring seamless integration with diverse platform services and establishing scalable LLMOps pipelines in production.
• Lead initiatives to tune, optimize, and deploy agentic applications in production with a focus on performance, reliability, and security.
• Collaborate with product, platform engineering, and security teams to ensure solutions are production-ready, resilient, and aligned with enterprise needs.

What you will do:

• Design and implement components across different layers of the stack using technologies such as Python, LangGraph, DSPy, and MCP.
• Collaborate with product teams to shape the future of Agentic AI and Auth for GenAI.
• Build reliable and scalable systems to run data processing pipelines, LLMOps infrastructure, and model inference systems.
• Utilize containerization technologies like Docker and orchestration tools like Kubernetes to manage and deploy these systems efficiently.
• Collaborate cross-functionally with product managers, researchers, and engineers to deliver secure, high-quality, and scalable AI/ML systems.
• Mentor and coach engineers, contributing to the growth of the team and the larger engineering community.

What you bring:

• Strong programming expertise in Python (and familiarity with Go or Typescript a plus).
• Proven experience building and deploying AI/ML systems at scale, including LLMOps, CI/CD, and infrastructure-as-code.
• Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.).
• Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows.
• Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration tools (Airflow, etc.).
• Experience with LiteLLM, LangGraph, LangChain, DSPy, LlamaIndex, MCP, or other related AI agent frameworks.
• Experience with containerized applications (Docker, Kubernetes) and cloud-native environments.
• Proven ability to collaborate with product and engineering teams to drive greenfield initiatives forward, navigate unknowns, and iterate quickly and frequently.
• Experience building tools or infrastructure for AI/ML applications, with a deep understanding of the developer lifecycle in an AI-native world.

Nice To Haves:

• Experience with identity and auth products.
• Experience creating tools that integrate with AI-based coding platforms.
• Experience with packaging and distributing containerized applications using Docker and Kubernetes.
• Familiarity with identity/authentication products and how they intersect with AI.
• Background in building AI-native developer tools or SDKs.

Please note that we encourage candidates to apply even if you do not have experience with all of the criteria or technologies listed above; these are provided to give insight into the tech stack and general responsibilities for the role.

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