Senior AI/ML Engineer

Senior MLOps Engineer - Intelligence Accelerator Join to apply for the Senior MLOps Engineer - Intelligence Accelerator role at Okta. About 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. About the Role The Intelligence Accelerator team in the Data Platform Group is the engine behind Okta’s AI/ML evolution. We are responsible for building the foundational AI/ML services and systems that fast‑track AI/ML for Okta and deliver differentiated value to our users. Working hand‑in‑glove with the Data Platform team, Data Scientists, Product Managers, and the SREs, you will bridge the gap between data, research and platform offerings, playing a critical role in enabling the technical adoption of ML and Generative AI across the company. We are assembling an elite unit designed to be fast, creative, and flexible. We practice extreme ownership. We expect great things from our engineers and reward them with stimulating challenges, novel technologies, and the chance to hold equity. Join the Intelligence Accelerator and help us change the cloud security landscape forever. As a Senior Machine Learning Engineer within the Intelligence Accelerator team, you will contribute to the development of our next‑generation AI/ML platform. You will work with the team to build the "paved road" that empowers Okta’s Applied AI teams to rapidly build and deploy intelligent features—enabling leveraging classical models, LLMs and autonomous agents. You will join a group that prioritizes engineering rigor—designing for scale, rigorous code reviews, automated testing, and CI/CD for ML (MLOps). In this role, you will: Responsibilities Contribute to the Foundation: Help design and maintain scalable infrastructure for core machine learning lifecycles, including distributed training clusters, real‑time inference serving, and high‑performance feature stores. Implement Agentic Infrastructure: Work on the bleeding‑edge stack for Agentic AI, helping to implement standards like the Model Context Protocol (MCP) to securely connect LLMs with internal tools, data, and APIs. Enable Applied AI: Build internal developer tooling that allows our product engineering teams to leverage Generative AI workflows, RAG pipelines, and vector databases without worrying about the underlying infrastructure. Architect & Deploy ML Infrastructure: Design, build, and maintain robust, scalable ML infrastructure using modern tools (Airflow, MLFlow, feature stores, vector databases) while implementing automated CI/CD workflows for model training, validation, and deployment. Drive Innovation & Security: Evaluate and adopt new ML technologies while ensuring data security, privacy, and compliance within the ML infrastructure. Build Scalable Data Pipelines: Design and maintain pipelines to ingest, process, and transform data from various sources and data warehouses, ensuring data quality, security, and compliance for data feeding into ML models and offline model artifact deployment. Optimize & Monitor Systems: Deploy and monitor ML systems with data scientists and engineers, troubleshoot infrastructure issues, and optimize their performance. Collaborate & Evangelize: Work with cross‑functional teams to align AI/ML platform strategies with company objectives while acting as an AI/ML evangelist and providing mentorship to analysts and stakeholders. Qualifications Engineering Experience: 5+ years of software engineering experience with a strong focus on backend systems, distributed computing, or cloud infrastructure (AWS/GCP/Azure). ML Infrastructure: Experience building and scaling ML platforms using technologies like Kubernetes, Ray, Kubeflow, or similar orchestration tools. Production Mindset: You treat infrastructure as code. You have a track record of implementing CI/CD pipelines, automated testing, and observability for Machine Learning workloads. GenAI Fluency: Familiarity with the modern LLM stack (e.g., LangChain, vector databases, RAG patterns) and an interest in emerging standards like Model Context Protocol (MCP) and Agentic workflows. Language Proficiency: Expert‑level proficiency in Python and familiarity with Go, Java, or C++. Collaborative Spirit: Experience working directly with Data Scientists or Applied AI teams to translate research needs into robust production systems. Nice to Have Experience with Java and/or Java EE web applications. Familiarity with authentication protocols, access management, or cloud security best practices. Exposure to prompt engineering, LLM ecosystems (Hugging Face, LangChain, vector databases), and identity and access management or security focused ML applications. This person must attend in‑person orientation in Toronto the first week of work. Salary Information The annual base salary range for this position for candidates located in the San Francisco Bay Area is between: $130,000—$194,000 CAD. Benefits Amazing Benefits Making Social Impact Developing Talent and Fostering Connection + Community at Okta Additional Information Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Some roles may require travel to one of our office locations for in‑person onboarding. Equal Opportunity Statement Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Personnel and Job Candidate Privacy Notice at https://www.okta.com/legal/personnel-policy/. Job ID P16359_3280416 #J-18808-Ljbffr