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.
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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.