What are the responsibilities and job description for the DEEP LEARNING INTERN position at Grainger?
Work Location Type : Hybrid As a leading industrial distributor with operations primarily in North America, Japan and the United Kingdom, We Keep The World Working by serving more than 4.5 million customers worldwide with products delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we're dedicated to providing value for customers, fostering an engaging culture for team members and driving strong financial results. Our welcoming workplace enables you to learn, grow and make a difference by keeping businesses running and their people safe. We're looking for passionate people to join our team as we continue leading the industry over our next 100 years. Key Responsibilities : Conduct fundamental and innovative research in applied machine learning Assist in the productionization of ML models and solutions when required Formulate approaches to solve complex problems using well-defined algorithms and data sources Perform data exploration to uncover new questions or opportunities within your problem area Propose and evaluate the applicability and limitations of data in various contexts Collaborate with cross-functional teams to integrate ML solutions into existing systems Qualifications : Currently pursuing MS / PhD in Engineering or Applied Sciences, preferably Computer Science, Electrical Engineering, or Physics / Mathematics Strong focus on Natural Language Processing (NLP) and Information Retrieval is highly desirable Proficiency in Python and SQL Experience building models using frameworks like PyTorch or TensorFlow Solid understanding of Unix command line for high performance computing Ability to explain both the intuition and mathematical foundations behind ML algorithms Strong grasp of concepts and foundations in discrete mathematics Required Skills : Strong programming skills in Python Proficiency in SQL for data manipulation and analysis Experience with common deep learning frameworks (PyTorch, TensorFlow) Familiarity with NLP techniques and information retrieval concepts Solid understanding of machine learning algorithms and their mathematical foundations Experience with Unix / Linux environments and shell scripting Preferred Skills : Familiarity with version control systems (e.g., Git) Experience with cloud computing platforms (AWS, GCP, or Azure) Knowledge of distributed computing frameworks (e.g., Spark) Experience with containerization technologies (e.g., Docker) Grainger is an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.
