Machine Learning Engineer at Workiva

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Machine Learning Engineer at Workiva. Location Information: USA. The . Machine Learning Engineer. is responsible for contributing to the development and implementation of frameworks to evaluate and monitor the innovative machine learning solutions at Workiva. They will assist in building the platform and metrics to evaluate and govern the ML/GenAI based solutions.. The role involves supporting the development of tools, systems, infrastructure, and automation to evaluate the performance and monitoring of applications. The Machine Learning Engineer will work closely with senior team members to troubleshoot issues related to accuracy, safety  latency  of ML based solutions. They will apply foundational knowledge in the Machine Learning space while learning from and assisting more experienced engineers.. What You'll Do. Assist in designing and maintaining systems that enable rapid ML development, with a focus on high availability, observability, scalability, and performance. Collaborate with product teams and architects to develop APIs, integrate ML solutions, and deliver complete software products aligned with customer needs. Contribute to the delivery, updates, and ongoing maintenance of ML infrastructure while writing high-quality, maintainable code. Write automated tests (unit, integration, functional) and participate in code reviews to ensure accuracy, stability, and adherence to best practices. Debug and troubleshoot ML components across diverse services and applications; partner with support teams to resolve production issues and ensure smooth operations. Participate in on-call rotations for 24x7 support of Workiva’s SaaS environments. Work closely with senior engineers to adopt team standards, processes, and technical practices while taking ownership of assigned activities. Explore and experiment with new technologies and techniques to continuously improve products and processes. Foster a collaborative and supportive team environment that values creativity, learning, and growth. What You'll Need. Preferred Qualifications. 2 years of ML engineering experience or; or an advanced degree without experience. Proficiency in the machine learning development cycle, toolsets, and applying ML solutions to real-world problems. Experience with model deployment, data pipelines, and CI/CD pipelines, as well as infrastructure management. Familiarity with Generative AI and relevant development patterns. Proficient in programming languages like Python, Java; experience using source control systems (e.g., GitHub). Experience in Machine Learning and LLM Evaluation metrics – RAGAS/ DeepEval Framework.. Experience in developing and implementing the framework for metrics evaluation and monitoring the ML/Gen AI based solutions. Hands-on experience with Docker and Kubernetes (preferred) along with cloud services like AWS or equivalent platforms. Strong foundation in programming, including data structures, algorithms, and distributed systems. Experience working in Agile/Sprint environments and debugging complex systems or applications. Knowledge of web protocols (HTTP), databases, performance tuning, and production-level testing. Knowledge of ISO42001 framework, Responsible AI standards and AI governance. Strong communication and organizational skills for managing multiple projects and meeting deliverables effectively. 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: $95,000.00 - $152,000.00. ✅ 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.. 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.. 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.. #LI-MJ2