Machine Learning Engineer

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Play a key role in the creation and execution of frameworks designed to assess and oversee the cutting-edge machine learning solutions at Workiva.

• Aid in the construction of the platform and metrics necessary for evaluating and governing ML/GenAI-based solutions.

• Contribute to the development of tools, systems, infrastructure, and automation aimed at assessing application performance and monitoring.

• Collaborate with senior team members to diagnose issues concerning the accuracy and latency of ML-based solutions.

• Acquire hands-on experience with Workiva’s technical standards and methodologies while taking responsibility for assigned tasks.

⛳️ Requirements

• A minimum of 2 years of experience in ML engineering or an advanced degree without prior experience.

• Expertise in the machine learning development cycle, toolsets, and the application of ML solutions to practical problems.

• Familiarity with model deployment, data pipelines, CI/CD pipelines, and infrastructure management.

• Understanding of Generative AI and associated development patterns.

• Proficient in programming languages such as Python and Java, with experience in source control systems (e.g., GitHub).

• Experience with Machine Learning and LLM Evaluation metrics such as RAGAS and the DeepEval Framework.

• Knowledge of web protocols (HTTP), databases, performance tuning, and production-level testing.

• Strong communication and organizational skills to effectively manage multiple projects and meet deadlines.

• Familiarity with the ISO42001 framework, Responsible AI standards, and AI governance and audits.

🏝️ Benefits

• Contribute to the design of systems that facilitate rapid machine learning (ML) development, with an emphasis on high availability and clear observability.

• Work alongside product teams to develop APIs that provide access to Workiva’s Gen AI/Agentic AI solutions and their evaluation.

• Write and maintain high-quality code, ensuring it is scalable, performant, and maintainable.

• Participate in code reviews, both giving and receiving constructive feedback.

• Create automated tests (unit, integration, functional) to guarantee stability and accuracy.

• Debug and troubleshoot ML components across various services and applications.

• Collaborate with support teams to resolve production issues and ensure seamless operations.

• Work with software and data architects, along with product managers, to deliver comprehensive software solutions that meet customer needs.