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. 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:
In your capacity as a Senior Machine Learning Engineer at Grainger, you will be central to the evolution and expansion of machine learning infrastructures, significantly elevating the customer journey. Your expertise will be critical in the implementation and ongoing refinement of ML Models and Services within the sphere of Product Discovery, which includes leveraging Generative AI, Natural Language Processing, Deep Learning, and Multi-Modal Models for enhanced Search, Recommendations, and Cross-Referencing functionalities. Through close collaboration with Machine Learning Scientists and Platform Engineers, you will pioneer sophisticated ML solutions, enabling seamless discovery of Grainger's diverse product offerings across various channels.
You Will:

• Deploy and maintain end-to-end machine learning systems at scale
• Contribute to ML system design and architecture of scalable AI/ML systems by working with ML platform engineers
• Design and implement robust data pipelines for training models and fine-tuning LLMs
• Solve high impact production ML problems and delivering business impact through data and machine learning products
• Collaborate with data scientists and machine learning engineers to ensure their models are production-ready and scalable and troubleshoot issues as they arise
• Keep up to date with the latest tools in the machine learning and MLOps space and recommend improvements and new solutions to enhance the platform

You Have:

• A bachelor's degree in computer science, Electrical Engineering, or related fields
• Proficiency developing production grade software incorporating testing and monitoring experience with Python
• Familiarity with common machine learning frameworks, tools, and patterns
• Experience with containerization and container orchestration technologies (e.g., Docker, Kubernetes, Airflow) and their application to machine learning workflows
• Experience with cloud-based services; AWS preferred (e.g., EKS, Lambda)
• Experience with CI/CD tools and deployment practices (e.g., Git, GitHub Actions)
• Experience with TensorFlow, PyTorch, or related deep learning frameworks
• Experience with MLOps and managing production machine learning lifecycle
• Experience with Messaging/Streaming Technologies (e.g., AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (e.g., DynamoDB, EKS, Graph database), and Microservices Architecture
• 5+ years of industry experience in deploying Machine Learning models to production at scale
• Experience with GPU/TPU training and optimizations

Rewards and Benefits:
With benefits starting day one, our programs provide choice and flexibility to meet team members' individual needs. Check out the highlights below and review all our benefits at GraingerTotalRewards.com .

• Medical, dental, vision, life, and pet insurance plans and 6 free sessions each year with a licensed therapist to support your emotional wellbeing
• Paid time off (PTO) and 6 company holidays per year
• 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no match required
• Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education and tools
• Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.
We are committed to fostering an inclusive, accessible environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment. With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.