The CIC Engineering Team

Okta's Customer Identity Cloud (CIC), is an easy-to-implement authentication and authorization platform designed by developers for developers. We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier-O global service to deliver convenience, privacy, and security so customers can focus on innovation.

Senior Machine Learning Engineer

The Machine Learning team is responsible for building ML models, leveraging Generative AI, and developing infrastructure and platform components to scale up AI/ML operations.

This Machine Learning Engineer role will help build and scale Generative AI use cases from integrating Large Language Models (LLM) to developing reusable platform components. The ideal candidate will have a deep technical background and hands-on experience in building and deploying AI/ML systems, as well as promoting a data-driven culture across the organization. They would not hesitate to wrangle data, if necessary, and are acutely familiar with what makes an effective and efficient ML team. They will also show passion generally for the field of applied AI/ML. Additionally, the candidate will have interest in learning about and potentially contributing towards cutting edge open source AI/ML technologies.

Responsibilities

• Design and implement infrastructure and platform components for leveraging LLM in production.
• Tune and optimize LLM to improve response quality and optimize performance.
• Build workflows and pipelines to process data from myriad sources into a knowledge base for various use cases.
• Collaborate with platform engineering teams to ensure that AI/ML systems integrate successfully into production environments while adhering to performance and availability SLOs.
• Participate in project planning, design, development, and code reviews.
• Communicate verbally and in writing to business customers and leadership teams with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations.
• Partnership across Engineering, Product Management, Security and Design teams to solve technical and non-technical challenges.

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Fluency in a computing language, e.g. Python, Scala, C , Java, etc.
• Knowledge of AWS Bedrock, OpenAI or similar Generative AI platforms.
• Experience with developing production AI/ML systems and platforms at scale, including retrieval-augmented generation (RAG) and embedding workflows.
• Experience with LLMOps, CI/CD, and IaC.
• Familiar with the full AI/ML lifecycle from model development, training, testing, deployment, monitoring, and iterating.
• Knowledge in prompt engineering and guardrails.
• Excellent verbal and written communication.
• Exceptional troubleshooting and problem solving skills, thrive in a fast-paced, innovative environment.

Preferred Qualifications

• Master's degrees in Computer Science, Engineering, or a related field.
• Familiar with training and fine tuning models at scale with experience in LLM evaluation.
• Experience with ML frameworks (e.g. TensorFlow, Spark ML, PyTorch), data workflow platforms (e.g. Airflow), and container technologies (e.g. Docker, Kubernetes).
• Familiar with Python and AI/ML libraries such as LangChain and FastAPI. .
• Ability to work with ambiguity, ability to self-motivate, prioritizing needs, and delivering results in a dynamic environment.
• Combination of deep technical skills and business savvy to interface with all levels and disciplines within our and our customer's organizations.

Required requirements:

• This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire.

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