Machine Learning Engineer

The Machine Learning Engineer is responsible for contributing to the development and implementation of innovative machine learning solutions at Workiva. They will assist in building ML features, collaborating on projects that may include integrating AI into Workiva's platform. The role involves supporting the development of tools, systems, infrastructure, and automation to enhance the performance and monitoring of ML solutions. The Machine Learning Engineer will work closely with senior team members to troubleshoot issues related to availability or scaling and contribute to solutions that ensure long-term stability. They will apply foundational knowledge in the Machine Learning space while learning from and assisting more experienced engineers. What You'll Do Assist in designing systems that enable rapid machine learning (ML) development, focusing on high availability and clear observability Collaborate with product teams to develop APIs for accessing Workiva's ML solutions Contribute to the delivery, update, and maintenance of ML infrastructure Write and maintain high-quality code, ensuring scalability, performance, and maintainability Participate in code reviews, offering and receiving constructive feedback Work closely with senior engineers to follow best practices and learn team processes Write automated tests (unit, integration, functional) to ensure the stability and accuracy of ML solutions Debug and troubleshoot ML components across different services and applications Engage with support teams in resolving production issues and ensuring smooth operation Take part in on-call rotations for 24x7 support of Workiva's SaaS environments Collaborate with software and data architects, as well as product managers, to help deliver complete software solutions that address customer needs Explore and experiment with new technologies and techniques to improve processes and products Foster an inclusive and collaborative work environment, contributing to team creativity and growth Gain hands-on experience with Workiva's technical standards and methods, while taking ownership of assigned activities What You'll Need Preferred Qualifications 2 years of ML engineering experience or; or an advanced degree without experience Proficiency in the machine learning development cycle, toolsets, and applying ML solutions to real-world problems Experience with model deployment, data pipelines, and CI/CD pipelines, as well as infrastructure management Familiarity with Generative AI and relevant development patterns Proficient in programming languages like Python, Java, Typescript, React, or similar, and experience using source control systems (e.g., GitHub) Hands-on experience with Docker and Kubernetes (preferred) along with cloud services like AWS or equivalent platforms Strong foundation in programming, including data structures, algorithms, and distributed systems Experience working in Agile/Sprint environments and debugging complex systems or applications Knowledge of web protocols (HTTP), databases, performance tuning, and production-level testing Strong communication and organizational skills for managing multiple projects and meeting deliverables effectively Travel Requirements and Working Conditions Willingness to travel up to 15% for team and corporate meetings, fostering relationships and representing company interests Reliable internet access for any period of time working remotely, as we embrace flexible work arrangements Workiva is an Equal Opportunity Employer.We believe that great minds think differently.We value diversity of backgrounds, beliefs, and interests, and we recognize diversity as an important source of intellectual thought, varied perspective, and innovation. Employment decisions are made without re