Staff Machine Learning Engineer, Workiva

• Bachelor’s degree in Computer Science, Engineering or equivalent combination of education and experience
• Minimum of 4 years in ML engineering or related software engineering experience
• Proficiency in ML development cycles and toolsets

Desirable

• Join our team at Workiva as a Staff Machine Learning Engineer!
• As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and delivery of groundbreaking machine learning solutions across our platform
• Your expertise will be instrumental in leading projects that demand innovative problem-solving, including the integration of cutting-edge Generative AI into our products
• In this role, you'll have the chance to develop robust tools, systems, and infrastructure to bolster the development, monitoring, and management of our machine learning solutions
• Leveraging your engineering prowess, you'll tackle challenges related to availability and scaling, ensuring the long-term stability of our systems
• Architect and deliver cutting-edge ML solutions using MLOps and best practices, fostering creativity in project execution
• Design systems to enable rapid ML development, high availability, and clear observability
• Develop tools, systems, and automation to support ML solutions, ensuring efficiency, scalability, and rapid development
• Collaborate closely with product teams to develop APIs, maintain ML infrastructure, and integrate machine learning features into products
• Provide technical leadership, mentor less experienced ML engineers and scientists, and define team best practices and processes
• Lead in the ML space by introducing new technologies and techniques, and applying them to Workiva's strategic initiatives
• Communicate complex technical issues to both technical and non-technical audiences effectively
• Collaborate with software, data architects, and product managers to design complete software products that meet a broad range of customer needs and requirements
• Deliver, update, and maintain machine learning infrastructure to meet evolving needs
• Host ML models to product teams, monitor performance, and provide necessary support
• Write automated tests (unit, integration, functional, etc.) with ML solutions in mind to ensure robustness and reliability
• Debug and troubleshoot components across multiple service and application contexts, engaging with support teams to triage and resolve production issues
• Participate in on-call rotations, providing 24x7 support for all of Workiva’s SaaS hosted environments
• Perform Code Reviews within your group’s products, components, and solutions, involving external stakeholders (e.g., Security, Architecture)