Staff Machine Learning Engineer, Okta

• Bachelor's degree in Computer Science, Engineering, Statistics or a related quantitative field
• Fluency in a computing language, e.g. Python, Scala, C++, Java, etc
• Experience with building production systems and platforms at scale
• Familiar with full AI/ML lifecycle from model development, training, testing, deployment, monitoring, and refining and iterating
• Knowledge in handling large datasets using SQL and databases in a business environment
• Excellent verbal and written communication
• Exceptional troubleshooting and problem solving skills
• Thrive in a fast-paced, innovative environment

Desirable

• The Machine Learning team is responsible for building machine learning models, and developing various infrastructure and platform components to scale up machine learning operations
• The Staff Machine Learning Engineer will help lead, build, scale and maintain the development and production platforms
• The ideal candidate will have a deep technical background and hands-on experience in building and deploying Machine Learning 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 machine learning team
• They will also show passion generally for the field of applied machine learning
• Additionally, the candidate will have interest in learning about and potentially contributing toward cutting edge open source Machine Learning and Data Science technologies
• Design and implement infrastructure and platform components for training, deploying, and monitoring machine learning models in production
• Build pipelines to ingest data from myriad sources into a centralized data lake for various use cases
• Collaborate with production engineering teams to ensure that machine learning models 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