About the role
Responsibilities Develop, implement, and validate machine learning models, training pipelines, and inference systems Implement or modify model components, data pipelines, and evaluation systems in Python Debug numerical, algorithmic, and system-level failures to find root causes Optimize model training and inference for memory, computation, and throughput Design and execute tests verifying implementation correctness Use coding agents in the development workflow while validating generated results Document technical approaches, decisions, test results and performance findings Requirements Master's degree or PhD in a quantitative discipline Strong professional or research experience in machine learning engineering Strong Python programming skills Hands-on experience using coding agents in a Python workflow Understanding of model training, inference and evaluation methods Strong quantitative reasoning and problem-solving skills Strong written and verbal English Availability for about 15 hours per week About the Company Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions.