ChargePoint Software Intern ML

About Company

As electric vehicles continue to gain momentum, they are projected to account for nearly 30% of all new vehicle sales by 2025 and over 50% by 2040. This rapid shift is turning electric mobility from a future concept into an everyday reality. ChargePoint (NYSE: CHPT) plays a key role in this transition by operating one of the largest EV charging networks globally. The company offers an end-to-end ecosystem that includes charging hardware, intelligent software, and user-friendly mobile solutions designed to support all types of charging needs across North America and Europe. By connecting drivers, businesses, automakers, utilities, policymakers, and other partners, ChargePoint is helping accelerate the adoption of sustainable and accessible electric transportation worldwide.

Job Overview

Company 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.

Roles & Resposibilties

• 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

Skills

• 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