Staff Machine Learning Engineer
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Job Description
Staff Machine Learning Engineer developing cutting-edge ML solutions integrating Generative AI for Workiva. Leading innovative projects ensuring ML infrastructure efficiency and stability.
Responsibilities:
- Architect and deliver cutting-edge ML solutions using MLOps and best practices
- 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)
Requirements:
- 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
- Experience building model deployment and data pipelines and/or CI/CD pipelines and infrastructure
- Proficiency in Python, GO, Java, or relevant languages
- 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.
Benefits:
- A discretionary bonus typically paid annually
- Restricted Stock Units granted at time of hire
- 401(k) match and comprehensive employee benefits package
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