Machine Learning Engineer

Position: Machine Learning Engineer Engagement Mode: Not specified Location: Not specified Position Overview: . The role involves assisting in building platforms and metrics to evaluate and govern ML/GenAI-based solutions, supporting the development of tools, systems, infrastructure, and automation to assess application performance and monitoring. The engineer will work closely with senior team members to troubleshoot issues related to accuracy, safety, and latency of ML-based solutions. This position requires applying foundational knowledge in the Machine Learning space while collaborating with product teams, software architects, data architects, and product managers to deliver complete software solutions that address customer needs. The role also includes on-call rotations for 24x7 support of Workiva's SaaS environments and active participation in an inclusive, collaborative team environment. Key Responsibilities: • 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 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 Required Skills 5+ years of experience with minimum 2 years of ML engineering experience, or an advanced degree • 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 • Proficiency in Python and Java programming languages • Experience using source control systems (e.g., GitHub) • Experience in Machine Learning and LLM Evaluation metrics – RAGAS/DeepEval Framework • Research and implementation of Agentic AI Evaluation and respective metrics • Experience in developing and implementing frameworks for metrics evaluation and monitoring of ML/Gen AI/Agentic AI/AaaS-based solutions • 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 • Strong communication and organizational skills for managing multiple projects and meeting deliverables effectively Preferred (Bonus) Skills: • Hands-on experience with Docker and Kubernetes • Experience with cloud services like AWS or equivalent platforms • Knowledge of ISO42001 framework • Knowledge of Responsible AI standards, AI governance, and Audits