Software Intern - ML

Confirmed live in the last 24 hours

ChargePoint

Bangalore, India

On-site

Posted April 1, 2026

Job Description

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

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