Staff Applied Machine Learning Scientist

at W.W. Grainger, Inc. in Chicago, Illinois, United States

Job Description

Work Location Type:Hybrid

About Grainger
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. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified company, we're looking for passionate people to join our team as we continue leading the industry over our next 100 years.
Position Details:
Grainger's Product Discovery team seeks a seasoned Senior/Staff Applied ML Scientist to develop cutting-edge recommendation solutions. Leveraging technologies such as Product Graphs, Deep Learning, Graph Neural Networks (GNNs), Large Language Models (LLMs), and Embeddings, our goal is to streamline operational efficiency and facilitate seamless customer experiences. At the heart of our mission, "We Keep the World Working," lies the crucial role of Search and Recommendations. Our innovative solutions enable customers to navigate through product categories effortlessly, discover premium products tailored to their needs, and access the most pertinent information, empowering them to make informed purchasing decisions confidently. The preference is for a work location in Chicago, IL on a hybrid basis 8 days a month and relocation assistance may be provided.

You Will:
Design, build, and maintain advanced machine learning models for our recommendation systems, ensuring they are scalable, efficient, and impactful.
Utilize a broad array of technologies including GNNs, LLMs, and Product and Graph Embeddings to enhance Grainger's product discovery experience, making it more intuitive and personalized for our customers.
Work closely with other ML scientists, engineers, and product managers to integrate your models into Grainger's platforms, contributing to a cohesive product discovery journey.
Keep abreast of the latest developments in machine learning and related technologies, applying cutting-edge research and methodologies to your work.
Work backward from customer use cases, engender implementation of ML models that solves the use cases at scale.
Articulate concepts and generate visual representations of your work and the impact it creates
Contribute to the strategic planning and direction of our ML initiatives, ensuring they align with business objectives and drive value
Share your knowledge and expertise with team members, fostering an environment of learning and growth within the Product Discovery teamYou Have:
Minimum of 7 years of experience in the industry delivering ML solutions
Master's or PhD degree in a field such as Applied Mathematics, Physics, Engineering, Computer Science, Electrical Engineering or equivalent experience
Ability to effectively communicate technical solutions to engineering teams and business audiences
Experience with deep learning frameworks such as PyTorch, Jax, TensorFlow, Keras
Familiarity with machine learning libraries and tools is essential for developing, training, and deploying models efficiently
Experience wrapping models in C/Python code and serving them as APIs
Experience optimizing inference speeds of models via quantization, distillation or other means when served as endpoints
Experience deploying models into the cloud with tooling like Docker & Kubernetes
Experience automating data augmentation and refresh using Airflow and Bash Scripting

Preferred:
Experience with GNNs to model relationships and interactions within data, crucial for building sophisticated recommendation systems based on Product Graphs
Familiarity with using Graphs for in-session recommendation or personalization
Understanding of LLMs, including their development and application in processing and understanding natural language, to enhance search and recommendation capabilities

Don't meet every single qualification? Studies show people are hesitant to apply if they don't meet all requirements listed in a job posting. If you feel you don't have all the desired experience, but it otherwise aligns with your background and you're excited about this role, we encourage you to apply. You could be a great candidate for this or other roles on our team.
Rewards and Benefits:
With benefits starting day one, Grainger is committed to your... For full info follow application link.

Grainger is an Equal Opportunity Workplace and an Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.