Workiva
Senior Staff Machine Learning Engineer - US
USA - Remote · Staff+
Sponsorship not specified$193k-$308kDetected 30 days ago
PythonJavaGoC++ScalaDistributed SystemsMachine LearningLLMsRAGAgentic AIMLOpsLeadershipMentoring
About the role
- 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.
Responsibilities
- Own the architecture of Workiva's AI platform and core AI services
- Lead the move from early adoption to production-grade, enterprise-ready systems
- Lead the design of enterprise agentic systems, including orchestration, workflow execution, memory, and multi-agent coordination
- Design and evolve Retrieval-Augmented Generation capabilities for enterprise content and knowledge workflows
- Partner closely with Product, Security, Infrastructure, and Architecture leaders
- Workiva is the platform designed to bring confidence, control, and a competitive edge to the world's most complex organizations.
- The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny.
- Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.
Requirements
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- 10+ years of software engineering experience, including large-scale SaaS platforms
- 5+ years designing, deploying, and operating production ML, AI, or data-intensive systems
- With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.
- Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.
Nice to have
- Experience designing and operating enterprise AI platforms, including model serving, evaluation, observability, and governance.
- Deep expertise in RAG, agentic systems, and large-scale knowledge systems
- Strong understanding of foundation model ecosystems, including inference, routing, prompting, and provider tradeoffs
- Experience with AI evaluation, secure AI systems, and regulated enterprise environments
- Proven track record leading architecture across multiple teams or platform domains
- Strong distributed systems, cloud-native, API, reliability, and operational excellence experience
- Expert-level Python proficiency and proficiency in at least one production language such as Java, Go, Scala, or C++
- Proven record mentoring senior engineers and technical leaders
Compensation
- $193,000.00 - $308,000.00 ✅ A discretionary bonus typically paid annually
- The salary range represents the low and high end of the salary range for this job in the US.
- The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.
Benefits
- ✅ Salary range in the US: $193,000.00 - $308,000.00 ✅ A discretionary bonus typically paid annually
- Shape how machine learning, Generative AI, and agentic systems are integrated across products
- ✅ Restricted Stock Units granted at time of hire
- ✅ 401(k) match and comprehensive employee benefits package
Company info
- Workiva is building a next-generation AI platform for mission-critical workflows used by some of the world's largest and most regulated organizations.
- We are seeking a Senior Staff Machine Learning Engineer to define how AI is architected, deployed, and trusted across our platform at enterprise scale, where accuracy, auditability, security, and reliability matter most.
Visa & Work Authorization
- ability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic
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This listing is sourced directly from Workiva's careers page and normalized into a canonical job model.