Deep Learning Intern

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Grainger is a leading broad line distributor with operations primarily in North America, Japan, and the United Kingdom. We achieve our purpose, We Keep the World Working®, by serving more than 4.5 million customers with a wide range of products that keep their operations running and their people safe. Grainger also delivers services and solutions, such as technical support and inventory management, to save customers time and money.

We're looking for passionate people who can move our company forward. As one of the 100 Best Companies to Work For, we have a welcoming workplace where you can build a career for yourself while fulfilling our purpose to keep the world working. We embrace new ways of thinking and recognize everyone is an individual. Find your way with Grainger today.

Position Details:

As a Deep Learning Intern, you will use multiple different technology platforms to build data-driven solutions and capabilities using machine learning and big data with a focus on Predictive Analytics, Deep Learning, Computer Vision, Natural Language Processing, and other relevant areas.

You Will:

• Plan, and communicate the results.
• Work to build state-of-the-art deep learning models to solve a wide array of business problems.
• Research and develop creative solutions to new and challenging problems.
• Use large pools of our data to fine tune neural networks for custom applications in computer vision and NLP.

You Have:

• Preferably purse a degree in Computer Science, Data Science, Mathematics, or related Engineering field
• Expected graduation with a master’s degree between Winter 2023 – Spring 2024
• Cumulative GPA of 3.0 or higher
• An interest in developing creative solutions
• Experience with Python programming
• Experience with open-source tool kits such as OpenCV, TensorFlow and Pytorch
• Knowledge and understating of machine learning techniques in computer vision and natural language processing
• Exposure to Flask applications, AWS, and deployment platforms (ML-OPS).