Application Guide
How to Apply for Summer 2026 Intern - Machine Learning
at Workiva
🏢 About Workiva
Workiva stands out by focusing specifically on integrated ESG (Environmental, Social, and Governance) reporting, helping organizations transparently communicate their climate impact and compliance efforts. Unlike general tech companies, Workiva operates at the intersection of technology, sustainability, and regulatory compliance, offering a mission-driven environment where technical work directly supports environmental transparency. This makes it particularly appealing for candidates interested in applying machine learning to solve real-world sustainability challenges.
About This Role
As a Machine Learning Intern at Workiva, you'll contribute to developing tools and libraries that support ESG reporting, working under the guidance of a full-time Machine Learning Engineer. You'll participate in the full development lifecycle—from discovery and prototyping to implementation and testing—while gaining hands-on experience with model deployment in a cloud environment. This role is impactful because your work will directly enhance the tools that help organizations measure and report their climate impact more accurately and efficiently.
💡 A Day in the Life
A typical day might start with a stand-up meeting to discuss progress on tooling tasks, followed by coding sessions to implement features for ML model development using Python or Go. You could spend time collaborating with a Machine Learning Engineer on prototyping new libraries, participating in code reviews, or updating tests, while using Docker for containerization and AWS for cloud-based deployments in a remote Agile environment.
🚀 Application Tools
🎯 Who Workiva Is Looking For
- A student pursuing a degree in computer science, statistics, or a related field with hands-on experience in Python and/or Go, demonstrated through projects or coursework.
- Someone familiar with the data science lifecycle and basic ML concepts, who can discuss practical applications (e.g., model training, evaluation) and has exposure to REST APIs for integrating ML services.
- A candidate with foundational experience in cloud platforms (AWS) and containerization tools like Docker, ideally shown through labs, personal projects, or prior internships.
- An individual comfortable working in Agile environments, with basic Git skills for version control and a collaborative mindset for code reviews and team-based development.
📝 Tips for Applying to Workiva
Highlight any projects or coursework related to ESG, sustainability, or regulatory compliance, as Workiva's focus on integrated reporting makes domain knowledge a plus.
Tailor your resume to emphasize hands-on experience with Docker/Kubernetes and AWS, even if from academic projects, as these are explicit requirements for tooling and deployment.
Include examples of participating in Agile methodologies or using task-tracking tools (e.g., Jira, Trello) in past roles or group projects to align with the job description.
Demonstrate your understanding of the data science lifecycle by describing a project where you followed stages from data collection to model deployment, linking it to Workiva's ML development needs.
If you have experience with Go (mentioned as an alternative to Python), showcase it prominently, as this might differentiate you in a Python-heavy applicant pool.
✉️ What to Emphasize in Your Cover Letter
["Express specific interest in Workiva's mission of ESG reporting and explain how your skills in ML and tooling can contribute to transparent climate impact solutions.", 'Detail a relevant project where you used Python/Go, Docker, or AWS to build or deploy ML models, emphasizing outcomes and collaboration (e.g., code reviews, testing).', "Connect your academic background (e.g., statistics, computer science) to the role's requirements, highlighting coursework or research in ML concepts and data science.", "Mention your ability to work in Agile teams and use source control (Git), providing a brief example of how you've contributed to collaborative development environments."]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Workiva's ESG reporting platform and recent case studies to understand how they integrate data and technology for compliance, noting any ML applications mentioned.
- → Review Workiva's blog or press releases for insights into their tech stack, especially around cloud infrastructure (AWS) and development practices, to tailor your interview responses.
- → Investigate the company's culture and values, particularly around sustainability and remote work, to align your application with their mission-driven environment.
- → Look into industry trends in ESG reporting and climate tech to discuss how ML can address challenges in this domain during interviews or in your cover letter.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic resume without tailoring it to highlight Python/Go, Docker, AWS, or Agile experience, as these are key requirements for this specific role.
- Failing to demonstrate practical experience with the data science lifecycle or ML concepts beyond theoretical knowledge, which could suggest a lack of hands-on skills.
- Overlooking the company's focus on ESG and compliance in application materials, making your interest seem misaligned with Workiva's mission-driven work.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!