Kodr

Machine Learning Engineer (m/f/d)

Remote

Full time

Remote

Energy

€80.000

My client supports companies with decarbonisation through a hybrid model that combines scalable software with expert guidance at every stage of the journey to net zero, from measuring and reducing emissions to supporting climate projects and transparent communication

Work closely across functions with data scientists, engineers, product managers, and business stakeholders to translate requirements into scalable technical solutions
Design, build, and operate reliable GenAI and ML systems, including cloud-based infrastructure and monitoring capabilities
Develop, train, and deploy machine learning models for benchmarking, recommendation, and forecasting use cases related to carbon footprint and emissions data
Implement automated testing, validation, and monitoring to ensure the accuracy, robustness, and reliability of AI solutions
Take end-to-end technical ownership, driving the full lifecycle from concept through deployment and ongoing operation, including associated project responsibilities
Stay current with advances in AI and machine learning and actively promote data science and ML best practices within the digital organisation

Work closely across functions with data scientists, engineers, product managers, and business stakeholders to translate requirements into scalable technical solutions
Design, build, and operate reliable GenAI and ML systems, including cloud-based infrastructure and monitoring capabilities
Develop, train, and deploy machine learning models for benchmarking, recommendation, and forecasting use cases related to carbon footprint and emissions data
Implement automated testing, validation, and monitoring to ensure the accuracy, robustness, and reliability of AI solutions
Take end-to-end technical ownership, driving the full lifecycle from concept through deployment and ongoing operation, including associated project responsibilities
Stay current with advances in AI and machine learning and actively promote data science and ML best practices within the digital organisation

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