Staff Machine Learning Engineer

- 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)

- 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

- Strong technical leadership skills in an Agile/Sprint working environment

- Experience building model deployment and data pipelines and/or CI/CD pipelines and infrastructure

- Proficiency in Python, GO, Java, or relevant languages, with experience in Github, Docker, Kubernetes, and cloud services

- Proven experience working with product teams to integrate machine learning features into the product

- Experience with commercial databases and HTTP/web protocols

- Knowledge of systems performance tuning and load testing, and production-level testing best practices

- Experience with Github or equivalent source control systems

- Experience with Amazon Web Services (AWS) or other cloud service providers

- Ability to prioritize projects effectively and optimize system performance

✅ Salary range in the US: $163,000.00 - $261,000.00 ✅ A discretionary bonus typically paid annually

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment. #LI-MJ2