Staff Full Stack – AI Engineer
Pocket Prep
MongoDBNode.jsNoSQLPythonTypeScript
Machine Learning Intern
Gridmatic
internship
Posted on:
Location: California • 🇺🇸 United States
Visit company websiteJob Level
Entry Level
Tech Stack
NumpyPandasPythonPyTorchScikit-LearnTensorflow
About the role
- Assist in designing and implementing machine learning models for electricity grid forecasting.
- Explore and prototype ML algorithms for generative time-series forecasting.
- Support the extension and improvement of existing ML libraries and frameworks.
- Run experiments and analyze results to improve model performance.
- Help monitor and evaluate the performance of production models.
- Contribute to team discussions, brainstorming, and problem-solving.
- We are seeking a motivated Machine Learning Intern to help design and test forecasting models that accelerate the decarbonization of the electricity grid. This role is ideal for students or recent graduates who want to apply their programming and analytical skills in a fast-paced environment, learn from experienced ML engineers, and contribute to solving real-world challenges in energy and climate. You will have the opportunity to work on cutting-edge problems in generative time-series forecasting, collaborate with a team of talented engineers and researchers, and see your ideas tested in real-world applications.
Requirements
- Currently pursuing or recently completed a BSc, MSc, or PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field.
- Strong foundation in math, probability, statistics, and algorithms.
- Proficiency in Python and familiarity with ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn, numpy, pandas).
- Good understanding of data structures and software engineering principles.
- Strong analytical and problem-solving skills.
- Excellent communication skills and ability to collaborate in a team environment.
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