Staff Machine Learning Engineer, Generative AI (Auth0)
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Role Overview
Okta seeks a Staff Machine Learning Engineer to architect, design, and deploy robust ML and GenAI systems. The role involves driving technical decision-making, leading initiatives, and collaborating with cross-functional teams to deliver secure, high-quality, and scalable AI/ML systems.
Key Skills for This Role
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About the Role
Okta seeks a Staff Machine Learning Engineer to architect, design, and deploy robust ML and GenAI systems. The role involves driving technical decision-making, leading initiatives, and collaborating with cross-functional teams to deliver secure, high-quality, and scalable AI/ML systems.
Responsibilities
- Architect, design, and deploy robust Machine Learning & GenAI systems, ensuring seamless integration with diverse platform services and establishing scalable LLMOps pipelines in production
- Drive technical decision making while striving to hit the right balance between factors such as simplicity, flexibility, reliability, and performance
- Lead initiatives to tune, optimize, and deploy agentic applications in production with a focus on performance, reliability, and security
- Partner with Product, Security, and Platform Engineering teams to design AI-powered experiences that are both innovative and trustworthy
- Design and implement scalable infrastructure and platform services for large-scale Generative AI use cases
- Collaborate cross-functionally with product managers, researchers, and engineers to deliver secure, high-quality, and scalable AI/ML systems
Requirements
- 7+ years of software development experience, with strong programming expertise in Python (and familiarity with Go or Typescript a plus)
- Hands-on experience with applied machine learning, from feature engineering to training and fine-tuning models
- 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
- Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI agent frameworks
- Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration tools (Airflow, etc.)
- Experience defining evaluation metrics, pipelines, and feedback loops for ML/GenAI systems
- 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
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