RWE

About the Company

RWE is leading the way to a clean energy world. With its investment and growth strategy Growing Green, RWE is contributing significantly to the success of the energy transition and the decarbonisation of the energy system. Around 20,000 employees work for the company in almost 30 countries worldwide. RWE is already one of the leading companies in the field of renewable energy. RWE is investing billions of euros in expanding its generation portfolio, in particular in offshore and onshore wind, solar energy and batteries. It is perfectly complemented by its global energy trading. RWE is decarbonising its business in line with the 1.5-degree reduction pathway and will phase out coal by 2030. RWE will be net-zero by 2040. Fully in line with the company’s purpose — Our energy for a sustainable life.

Listed Jobs

Company Name

RWE

Job Title

Machine Learning Research Intern

Job Description

Job title: Machine Learning Research Intern Role Summary: Conduct research and development of diffusion‑based generative models, ML pipelines, and supervised prediction models to improve wind turbine performance through atmospheric data analysis. Translate research into operational systems for wind energy portfolios. Expactations: Deliver reproducible, production‑ready code and models; collaborate with domain experts and data owners; maintain clean, version‑controlled repositories; operate independently while utilizing LLM tools for coding assistance. Key Responsibilities: - Design and train diffusion‑based generative models for high‑resolution wind field reconstruction and downscaling. - Build supervised and unsupervised ML pipelines for cleaning and processing meteorological time‑series and metadata. - Develop supervised learning models predicting power‐performance losses linked to atmospheric variables. - Write object‑oriented Python code using TensorFlow/Keras, NumPy, Pandas, xarray, and supporting scientific libraries. - Manage code quality through GitHub pull requests, reviews, and version control workflows. - Collaborate with data owners and domain experts to acquire, understand, and preprocess real operational datasets. - Integrate research outputs into existing operational pipelines and validate model performance. Required Skills: - Strong Python programming with TensorFlow/Keras, NumPy, Pandas, and scientific libraries. - Experience or familiarity with diffusion or other generative models. - Proficient in object‑oriented programming concepts. - Solid Git/GitHub workflow experience (branching, PRs, code reviews). - Ability to work effectively with noisy, real‑world datasets. - Good written and verbal communication skills. - Team‑oriented, self‑driven curiosity. - Domain expertise or strong interest in atmospheric science, physics, or renewable energy systems. - Knowledge of mesoscale or reanalysis models (e.g., WRF, ERA5). - Familiarity with uncertainty quantification or physics‑informed ML is a plus. - Experience translating research into operational production pipelines is preferred. Required Education & Certifications: - Current enrollment or recent graduate in Computer Science, Data Science, Engineering, Information Science/Technology, Physics, Atmospheric Science, or related field. - Strong academic record in machine learning, AI, or statistics coursework. - No mandatory certifications required, but familiarity with TensorFlow/Keras SDK or related ML frameworks is essential.

Austin, United states

On site

Fresher

02-02-2026