Machine Learning Engineer

Description

Summary: The Machine Learning Engineer will develop and implement frameworks for evaluating and monitoring innovative machine learning solutions, focusing on GenAI and Agentic AI. Highlights: 1. Develop and implement ML/GenAI evaluation and monitoring frameworks 2. Collaborate on GenAI/Agentic AI solutions and their evaluation APIs 3. Gain hands-on experience with technical standards and methods 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