Staff Machine Learning Engineer

Join us at Workiva as we take bold steps to shape the future of enterprise collaboration and decision automation.

We’re hiring a Staff Machine Learning Engineer to help design and build advanced AI capabilities at the core of Workiva’s evolving platform. This is a high-impact opportunity to apply your ML expertise, full-stack thinking, and systems mindset in a fast-paced, forward-looking environment. You’ll work closely with a cross-functional team of product, platform, and engineering leaders to bring cutting-edge ML solutions to life in ways that scale across our suite of enterprise applications.

We're looking for someone with deep technical skills, a product mindset, and the curiosity and drive often found in startup environments. If you’re someone who enjoys wearing multiple hats and thrives in spaces where innovation and ambiguity intersect—this could be a great fit.

Why Join Workiva

• Meaningful Impact: Work on intelligent features that empower transparency, accuracy, and confidence in financial and sustainability reporting

• Innovation at Scale: Contribute to a highly modular, flexible ML architecture that will evolve alongside customer needs

• Autonomy & Growth: Be part of a lean, fast-moving AI team where initiative and creativity are valued

• Future-Facing Work: Build the ML systems and infrastructure that will power Workiva’s next decade of product innovation
   

What You’ll Do

Architect & Build AI Solutions

• Design and implement end-to-end ML systems used across Workiva’s platform

• Fine-tune large language models (LLMs) and develop agentic systems to support intelligent automation

• Build scalable infrastructure for experimentation, deployment, and monitoring of ML capabilities

• Contribute to the evolution of a composable, extensible ML platform used by multiple products
   

Collaborate Across Teams

• Partner with product managers, designers, and platform engineers to turn vision into reality

• Communicate design decisions, trade-offs, and results clearly across technical and non-technical audiences

• Provide mentorship and share best practices in ML system design and engineering
   

Prioritize Trust, Security, and Performance

• Develop and maintain robust testing and observability frameworks to ensure reliability and safety of ML systems

• Incorporate ethical considerations, security standards, and bias mitigation strategies from the outset

• Continuously improve deployment pipelines and data flows with scalability and transparency in mind
   

What You’ll Need

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field (advanced degrees welcome)

• 4+ years of experience in machine learning engineering or related software roles

• Strong experience with ML lifecycle, tooling, and infrastructure

• Proficiency in Python and at least one statically typed language (e.g., Go, TypeScript, Rust, Java)
   

Preferred Qualifications

• LLM Fine-Tuning Mastery – You’ve tuned transformer-based models and understand the nuances of prompt engineering and training trade-offs

• Agentic AI Experience – Experience with frameworks like LangChain, AutoGPT, CrewAI, or similar for orchestrating complex workflows

• Hands-On System Design – You can architect distributed systems and bring them to life with tools like Terraform, Docker, and cloud services

• Polyglot Coding Chops – You bring depth in Python and at least one additional language (Go, TypeScript, Rust, Java—surprise us!)

• Data-Wrangling Mojo – You know your way around structured and semi-structured data using tools like Pandas, DuckDB, or Apache Arrow

• Security & Ethics Awareness – You proactively address concerns around PII, hallucinations, and responsible AI

• Startup Mindset – You’re action-oriented, comfortable with ambiguity, and quick to experiment and learn

• Communication Superpower – You can make complex AI concepts understandable to any stakeholder

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