Machine Learning Scientist

Overview

As a Machine Learning Scientist at EDF, you will develop and apply data-driven solutions across the company’s digital initiatives. You will work in a multidisciplinary Digital Innovation team to test ideas, build ML models and production-ready solutions that address real business challenges. You’ll explore computer vision, NLP and generative AI to support EDF’s transition to An Electric Britain. This role combines hands-on modelling with collaboration, experimentation and impact at scale.

Pay / Benefits

• competitive starting salary
• annual bonus potential
• market-leading pension
• electric vehicle leasing
• discounted gym membership
• life assurance

Responsibilities

• Design, develop and adapt machine learning models to solve complex business challenges
• Explore and implement AI applications including CV, NLP and generative AI
• Build proofs of concept and deliver production-ready data science solutions
• Work with large, diverse datasets to extract insights and support data-driven decisions
• Collaborate with multidisciplinary teams and external partners on innovation projects

Key requirements

• Master’s degree in Computer Science, Data Science, Mathematics or related data-intensive discipline
• Experience building and adapting ML models, including transfer learning, training, fine-tuning, evaluation metrics, and explainability techniques
• Experience applying ML in computer vision or natural language processing
• Proficiency with Python data science libraries (pandas, scikit-learn, statsmodels, matplotlib, seaborn) and DL frameworks (TensorFlow, PyTorch)
• Experience working with large datasets, data warehouses, big data technologies, and ML solutions
• Ability to design and build complex models capable of operating autonomously on large datasets
• Experience finding, assessing and adapting open-source solutions

• Curious and adaptable
• Ability to learn and apply emerging technologies quickly
• Collaborative, with experience in multidisciplinary teams
• Python data science stack (pandas, scikit-learn, statsmodels, matplotlib, seaborn)
• TensorFlow or PyTorch
• Computer vision or natural language processing

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