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Workiva

Senior Machine Learning Engineer

Sorry, this job was removed at 08:12 a.m. (MST) on Wednesday, May 28, 2025
Remote
Hiring Remotely in USA
128K-205K Annually
Remote
Hiring Remotely in USA
128K-205K Annually

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Lead the Machine Learning team at Workiva, integrating Generative AI into products, ensuring system reliability, and fostering team development.
Top Skills: AgileApi DevelopmentAWSAzureGCPGenerative AiMachine LearningSaaS

We're looking for a Senior Engineer to join our Machine Learning team and help build the next generation of intelligent solutions at Workiva. In this role, you’ll play a key part in designing, developing, and delivering machine learning infrastructure and services—including innovative applications of Generative AI—that power impactful features across our platform.

As a senior machine learning engineer, you’ll work closely with cross-functional teams to create scalable, high-performance systems that support the full ML lifecycle—from experimentation and training to deployment and monitoring. Your work will directly contribute to delivering smarter, faster, and more intuitive experiences for our customers.

If you're excited by the potential of AI and want to build real-world solutions at scale, we’d love to have you on the team. Explore the possibilities of Workiva’s Generative AI at Workiva and help shape the future of enterprise technology 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 and Lead

  • Collaborate closely with product teams to develop APIs, maintain ML infrastructure, and integrate machine learning features into products

  • Mentor less experienced ML engineers and scientists, and define team best practices and processes

  • 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

Ensure Reliability and Support

  • 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) 

What You'll Need

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Engineering or equivalent combination of education and experience

  • Minimum of 2 years in ML engineering or related software engineering experience

  • Proficiency in ML development cycles and toolsets

Preferred Qualifications

  • Experience with Generative AI

  • Experience working 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

Travel Requirements and Working Conditions

  • Willingness to travel up to 10% 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

How You’ll Be Rewarded

✅ Salary range in the US: $128,000.00 - $205,000.00

✅ A discretionary bonus typically paid annually

✅ Restricted Stock Units granted at time of hire

✅ 401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Workiva is an Equal Employment Opportunity and Affirmative Action 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 regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression genetic information, marital status, citizenship status or any other protected characteristic.  We strongly encourage and welcome people from historically marginalized groups to apply.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email [email protected].
 

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

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

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