At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.
Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.
Reports To
Director, NOC Delivery & Automation
What You Will Be Doing
We’re looking for an AI/Machine Learning Intern to join our team and work on building intelligent systems that solve real-world problems. You’ll gain hands-on experience developing, training, and deploying machine learning models while collaborating with experienced engineers and data scientists.
What You Will Bring to ChargePoint
Develop and train machine learning models for classification, regression, and NLP tasks
Preprocess, clean, and analyze datasets to extract meaningful insights
Experiment with model architectures and hyperparameter tuning to improve performance
Build and maintain data pipelines for model training and inference
Document experiments, results, and methodologies for reproducibility
Requirements
Strong programming skills in Python
Basic knowledge of statistics and linear algebra
Hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
Understanding of core ML concepts including supervised/unsupervised learning, neural networks, and model evaluation metrics
Familiarity with data manipulation using Pandas and NumPy
Experience with natural language processing (NLP) using libraries like Hugging Face Transformers, spaCy, or NLTK
Familiarity with computer vision frameworks and techniques (OpenCV, CNNs, YOLO, or torchvision)
Experience with vector databases (Pinecone, Weaviate, ChromaDB) for semantic search
Knowledge of diffusion models (Stable Diffusion, DALL-E) or GAN architectures
Hands-on experience with LLMs (GPT, Claude, Llama) and prompt engineering
Experience with cloud platforms (AWS, GCP, Azure) for ML workloads
Knowledge of MLOps practices including model versioning, experiment tracking (MLflow, Weights & Biases), and deployment
Published research or personal projects demonstrating ML expertise
Participation in Kaggle competitions or similar challenges
Educational Qualifications
Currently pursuing B.Tech/M.Tech in Computer Science, Data Science, Artificial Intelligence, Mathematics, or related field
Minimum 90% or 9.0 CGPA in current degree program
Minimum 90% in Class XII / Class X (or equivalent)
No active backlogs at the time of application
Location
Bangalore