Requirements
Must have:
- We require a bachelors degree in Computer Science, Engineering, or an equivalent blend of education and experience.
- We need at least 4 years of experience in machine learning engineering or a related software engineering field.
- We expect proficiency with ML development lifecycles and the associated tooling.
- Preferred experience includes familiarity with Generative AI.
- Strong technical leadership in an Agile or Sprint-based environment is highly valued.
- Experience building model deployment pipelines, data pipelines, and/or CI/CD infrastructure is preferred.
- We value proficiency in Python, Go, Java, or similar languages, along with hands-on experience with GitHub, Docker, Kubernetes, and cloud platforms.
- Prior success partnering with product teams to embed machine learning capabilities into products is preferred.
- Experience with commercial databases and HTTP/web protocols is an asset.
- Knowledge of performance tuning, load testing, and production-grade testing practices is desirable.
- Familiarity with GitHub or comparable source control systems is preferred.
- Experience with AWS or another cloud provider is a plus.
- We are looking for someone who can prioritize effectively and optimize system performance.
- Less than 10% travel and reliable internet access are required for this remote-friendly role.
Responsibilities:
- We architect and deliver advanced machine learning solutions using MLOps and established best practices.
- We design systems that support rapid ML development, high availability, and strong observability.
- We build tools, services, and automation that improve efficiency, scalability, and development speed for ML work.
- We partner closely with product teams to develop APIs, maintain ML infrastructure, and integrate machine learning features into our products.
- We provide technical leadership, mentor junior ML engineers and scientists, and help establish team processes and standards.
- We introduce new technologies and techniques to support Workivas strategic machine learning initiatives.
- We communicate complex technical topics clearly to both technical and non-technical audiences.
- We collaborate with software engineers, data architects, and product managers to design end-to-end products that meet customer needs.
- We deliver, update, and maintain ML infrastructure as requirements evolve.
- We host ML models for product teams, monitor performance, and provide ongoing support.
- We write automated tests, including unit, integration, and functional testing, to strengthen reliability.
- We debug and troubleshoot issues across multiple services and applications, working with support teams to resolve production problems.
- We participate in on-call rotations to provide 24x7 support for our SaaS-hosted environments.
- We perform code reviews across our products, components, and solutions, engaging stakeholders such as Security and Architecture when needed.
Company:
We are Workiva, a platform built to give complex organizations confidence, control, and a competitive edge. Our AI-powered platform connects finance, risk, and sustainability on one secure foundation so data stays trusted, traceable, and ready for action.
We offer a competitive US salary range of $163,000 to $261,000, an annual discretionary bonus, restricted stock units at hire, a 401(k) match, and a comprehensive benefits package. We support employees working from an office or remotely from any location within their country of employment, and we ask all employees to complete security and privacy training aligned to their roles. We are committed to equal opportunity, reasonable accommodations, and building technology that helps leaders make decisions with confidence.
