Full Time AI Test Engineer - Machine Learning QA Analyst - AI Validation Engineer Jobs, in Opus Traffic Management Solutions - Maukerja

Role Description This is a full-time remote role for an AI Test Engineer / Machine Learning QA Analyst / AI Validation Engineer. The role involves designing and executing test plans for AI and machine learning models used in traffic management and related operational systems, with a focus on reliability, accuracy, and safety. Responsibilities include building automated test frameworks, validating model performance against defined metrics, performing regression and stress testing, and analyzing edge cases and failure modes. The role also includes collaborating with data science and engineering teams to review model designs, refine datasets, and improve algorithms based on test findings, as well as documenting test results and creating clear reporting for technical and non-technical stakeholders. The individual will help define quality standards for AI components and contribute to continuous improvement of processes, tools, and validation methodologies.

Qualifications

• Strong foundation in Computer Science and Algorithms, with the ability to design efficient test and validation workflows.
• Knowledge of Neural Networks and Pattern Recognition to understand, evaluate, and challenge model behaviors.
• Proficiency in Statistics for model performance analysis, metric design, and interpreting experimental results.
• Experience with software testing or QA for machine learning systems, including automated testing and CI/CD integration.
• Hands-on experience with programming languages commonly used in ML (such as Python) and relevant libraries or frameworks.
• Familiarity with data pipelines, data quality assessment, and handling large datasets for training and validation.
• Ability to communicate complex technical findings clearly to both technical and non-technical audiences.
• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field; equivalent practical experience is also valued.
• Experience in safety-critical or infrastructure-related domains (e.g., transportation, utilities, construction) is beneficial.
• Comfort working independently in a remote environment and collaborating effectively across distributed teams.