Manager, Applied Machine Learning

Work Location Type: Remote  

Req Number 324180

About Grainger

W.W. Grainger, Inc., is a leading broad line distributor with operations primarily in North America, Japan and the United Kingdom. At Grainger, We Keep the World Working® by serving more than 4.5 million customers worldwide with products and solutions delivered through innovative technology and deep customer relationships. Known for its commitment to service and award-winning culture, the Company had 2024 revenue of $17.2 billion across its two business models. In the High-Touch Solutions segment, Grainger offers approximately 2 million maintenance, repair and operating (MRO) products and services, including technical support and inventory management. In the Endless Assortment segment, Zoro.com offers customers access to more than 14 million products, and MonotaRO.com offers more than 24 million products. For more information, visit www.grainger.com.  

Compensation

The anticipated base pay compensation range for this position is $145,700.00  to $242,800.00.

Rewards and Benefits

With benefits starting on day one, our programs provide choice and flexibility to meet team members' individual needs, including:

• Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
• 18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.
• 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution 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.

For additional information and details regarding Grainger’s benefits, please click on the link below:

https://experience100.ehr.com/grainger/Home/Tools-Resources/Key-Resources/New-Hire

The pay range provided above is not a guarantee of compensation.  The range reflects the potential base pay for this role at the time of this posting based on the job grade for this position. Individual base pay compensation will depend, in part, on factors such as geographic work location and relevant experience and skills.   

The anticipated compensation range described above is subject to change and the compensation ultimately paid may be higher or lower than the range described above. 

Grainger reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion at any time, consistent with applicable law.  

Position Detail

We are looking for a highly motivated Manager, Applied Machine Learning Science to lead a team of world-class machine learning scientists and engineers. You will drive initiatives that design, develop, and deliver scalable ML and AI solutions that directly shape business decisions, improve operational effectiveness, and unlock new value across the company. Combining both a strong technical depth with leadership and vision — guide a team that builds high-impact ML products and infrastructure, while fostering a culture of experimentation, learning, and continuous improvement. You will identify new opportunities where ML, optimization, and intelligent automation can transform the business, and work cross-functionally to turn those ideas into production-ready solutions.

You Will

• Own the end-to-end relationship with business partners — understanding complex problems, identifying opportunities, and translating them into scalable ML solutions
• Lead, mentor, and grow a team of machine learning scientists and engineers; set direction, define priorities, and foster technical excellence and collaboration
• Drive the design, development, and delivery of scalable machine learning and deep learning models that improve the effectiveness and efficiency of core business operations
• Oversee the creation of robust ML pipelines — from ideation and prototyping to automated, production-grade systems
• Apply advanced methods such as classification, regression, NLP, deep learning, LLMs, time series forecasting, and Bayesian inference to build impactful solutions
• Encourage and support the development of interactive analytical tools (e.g. React, Streamlit) to visualize model outputs and enhance collaboration with business users
• Explore and apply optimization, simulation, and decision-science techniques to augment predictive models with prescriptive intelligence
• Implement rigorous model validation, monitoring, and continuous improvement practices (e.g., drift detection, retraining, hyperparameter tuning)
• Promote automation and standardization across ML workflows to improve scalability and reproducibility
• Stay current with emerging ML/AI technologies and research, evaluating their potential to drive innovation and competitive advantage
• Communicate analytical insights, model performance, and business impact clearly to executives and stakeholders

You Have

• MS degree or PhD in Mathematics, Data Science, Applied Analytics, Operations Research, Computer Science, Applied Science, or Engineering
• 5+ year’s of hands-on experience delivering production-grade machine learning solutions at scale
• Previous experience leading, mentoring, and developing a high-performing ML/AI team
• Advanced proficiency in Python and SQL for data manipulation and model development
• Hands-on experience with machine learning frameworks and deployment tools (e.g., scikit-learn, PyTorch, TensorFlow, MLflow, REST APIs)
• Familiarity with containerization, CI/CD, and version control (Kubernetes, Docker, Git)
• Experience building interactive, model-driven applications using React, Streamlit, or similar frameworks
• Proven ability to apply deep learning and transformer-based modeling methods in production environments
• Strong analytical and problem-solving mindset; able to translate complex business challenges into structured, data-driven solutions
• Solid understanding of MLOps practices, model registry, drift monitoring, and hyperparameter optimization
• Experience with databases (Teradata, Snowflake, S3) and data processing at scale
• Strong understanding of modern ML architectures, including embedding models, multimodal systems, or generative AI (LLMs, diffusion models) where applicable.
• Proven ability to lead cross-functional collaborations and influence technical and business stakeholders
• Excellent communication skills, with the ability to convey technical concepts to both technical and business audiences

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace.

We are committed to fostering an inclusive, accessible work 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, should you need a reasonable accommodation during the application and selection process, including, but not limited to use of our website, any part of the application, interview or hiring process, please advise us so that we can provide appropriate assistance.

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