Applied Machine Learning Scientist- GenAI

About Grainger W.W. Grainger, Inc. is a leading broad line distributor with operations primarily in North America and Japan. At Grainger, We Keep the World Working® by serving more than 4.6 million customers worldwide with maintenance, repair and operating (MRO) products and value‑added solutions delivered through innovative technology and deep customer expertise. Known for its commitment to service and purpose-driven culture, the Company reported 2025 revenue of $17.9 billion.

For more information, visit

Work Location Type: Remote

Req Number: 330464

Compensation
The anticipated base pay compensation range for this position is $ – $. This role is eligible for an incentive target of up to 15% based on the achievement of individual and company performance objectives in accordance with the current terms of the incentive program which are subject to change.

Sponsorship
This position is not eligible for any form of sponsorship now or in the future. Individuals requiring sponsorship (e.g. OPT or H1B visa status) should not apply. Only individuals authorized to work in the United States now and for the foreseeable future will be considered for this position.

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:

Grainger Benefits
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.

Grainger’s Sales Machine Learning team is seeking a Staff Applied Machine Learning Scientist to serve as a technical leader for Generative AI and agentic AI applications across the Sales domain. In this role, you will help design and build Grainger’s Sales AI platform, enabling 3,000+ sellers to work more productively, serve customers more effectively, and drive measurable business growth.

You will lead the development of scalable AI systems that combine LLMs, machine learning models, retrieval, tools, APIs, workflow orchestration, evaluation, and monitoring. The work focuses on building production‑ready virtual assistants and deep agents across mobile and web experiences. You will set the technical direction, establish patterns for reliable and governed AI systems, mentor engineers, and partner with product, engineering, design, and business stakeholders to turn high-value Sales opportunities into production-ready AI capabilities.

The work location is Chicago, IL on a hybrid basis (8 days per month). We will consider highly qualified candidates who are remote, provided they can come onsite during orientation and travel for team meetings, estimated at once per quarter.

• Design, develop, and maintain both traditional and cutting‑edge machine learning models that solve real-world business problems—ensuring scalability,…