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Job Type
Full Time
Job Details
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 need to bring not just senior-level experience, but a deep understanding of system design principles and a track record of architecting robust ML solutions. We're looking for someone who can mentor and lead projects, driving the development of exceptional talent while ensuring project success. Additionally, experience with Terraform or CloudFormation for deploying infrastructure is crucial. We're seeking candidates who can efficiently manage infrastructure deployment using these tools to support our ML initiatives.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.If you're passionate about pioneering the possibilities of Generative AI and want to be part of a team driving innovation at Workiva, we invite you to join us! Learn more about Workiva's Generative AI and be part of shaping the future of ML with us. What You’ll Do Architect and Develop Solutions
- 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
- Proficiency in ML development cycles and toolsets
- Familiarity with Generative AI
- Strong technical leadership skills in an Agile/Sprint working environment
- Proven experience working with product teams to integrate machine learning features into the product
- 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
- 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
- Less than 10% travel
- Reliable internet access for remote working opportunities
About the Company
Workiva
Ames, IA, United States
We founded Workiva to transform the way people manage and report business data with various collaborators, data sources, documents, and... Read more