Open role

Machine Learning Engineer (m/f/d)

At a glance

Remote

Full time

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

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related discipline
At least 3 years of professional experience in a machine learning role (e.g. Data Scientist, Software Engineer, ML/AI Engineer), ideally within a startup or scale-up environment
Proven experience designing, building, and operating production-grade machine learning and generative AI systems at scale, with a strong focus on reliability, validation, and monitoring
Solid understanding of core machine learning techniques, including regression, classification, time series forecasting, recommendation systems, and outlier detection
Hands-on experience with generative AI, including large language models, embeddings, and frameworks such as LangChain or LlamaIndex
Strong proficiency in Python and common machine learning libraries (e.g. scikit-learn, PyTorch, TensorFlow), as well as experience working within the AWS ecosystem
Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams
Very good command of written and spoken English

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