We are looking for candidates with experience in ML infrastructure, LLM evaluation (RAGAS/DeepEval), GenAI/Agentic AI, and strong Python/Cloud background.
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 systems that enable rapid machine learning (ML) development, focusing on high availability and clear observability
Collaborate with product teams to develop APIs for accessing Workiva’s Gen AI/ Agentic AI solutions and the respective evaluation.
Contribute to the delivery, update, and maintenance of ML infrastructure
Write and maintain high-quality code, ensuring scalability, performance, and maintainability
Participate in code reviews, offering and receiving constructive feedback
Work closely with senior engineers to follow best practices and learn team processes
Write automated tests (unit, integration, functional) to ensure the stability and accuracy
Debug and troubleshoot ML components across different services and applications
Engage with support teams in resolving production issues and ensuring smooth operation
Take part in on-call rotations for 24x7 support of Workiva’s SaaS environments
Collaborate with software and data architects, as well as product managers, to help deliver complete software solutions that address customer needs
Explore and experiment with new technologies and techniques to improve processes and products
Foster an inclusive and collaborative work environment, contributing to team creativity and growth
Gain hands-on experience with Workiva’s technical standards and methods, while taking ownership of assigned activities
Requisitos:
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. Research and Implement Agentic AI Evaluation and the respective metrics
Experience in developing and implementing the framework for metrics evaluation and monitoring the ML/Gen AI/Agentic AI/ AaaS 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, AI governance & Audits
Strong communication and organizational skills for managing multiple projects and meeting deliverables effectively
English proficiency