Manager, Applied Machine Learning

Work Location Type: Hybrid  

Req Number  328783

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 $148,900.00 – $248,200.00. This role is eligible for an incentive target of up to 15% of base compensation, 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.

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:

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

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.

Position Details:

Grainger's Product Discovery team seeks a seasoned Manager, Applied ML Scientist to drive cutting-edge generative AI solutions. We're building AI agents that assist our human customer service agents in real-time during customer phone calls. The AI agents need to surface product information, detect customer sentiment, recommend next-best-action, and automate post-call documentation. This role is to lead the team building the ML systems that power these capabilities; we are looking for someone equally comfortable leading a team and building themselves.

You'll work at the intersection of real-time ML inference, event-driven architectures, and contact center operations. The voice channel is in early-stage development, so you'll have significant influence over architectural decisions and technical direction.

Chicago, IL is the preferred location with a hybrid work environment (2 days per week in the Merchandise Mart downtown Chicago office). We will also consider highly qualified remote candidates who are willing to travel to Chicago for onboarding and occasional team meetings. Onsite onboarding will be required.

You Will:

• Stand up and develop a team to support the customer service voice project
• Work with Product leaders to understand business objectives and communicate those to your team
• Manage relationships with Software Engineering, Machine Learning Operations and Data Engineering
• Design, train, and deploy ML models for voice-specific use cases: real-time intent classification, sentiment/tonality detection, escalation prediction, and conversational Q&A
• Build and optimize production inference pipelines with tight latency requirements
• Develop event-driven data pipelines that process streaming transcription data from Genesys through EventBridge into persistent state stores
• Implement model monitoring, evaluation frameworks, and drift detection for voice-specific metrics
• Collaborate with Software Engineering on API design, WebSocket integrations, and UI data contracts
• Build automated retraining pipelines using call outcome feedback and human-labeled escalation data

You Have:

• 5+ years in ML Engineering/Applied ML with at least 2 years deploying models to production at scale
• Hands-on experience with LLM/SLM fine-tuning and prompt engineering depending on latency/cost tradeoffs
• Production model serving experience: Triton Inference Server, vLLM, TensorRT, or similar low-latency serving infrastructure
• Strong Python fundamentals with experience in PyTorch for model development
• Agentic AI frameworks: LangGraph, LangChain, or custom agent orchestration
• Event-driven architecture experience: Kafka, AWS EventBridge, SQS, or similar message/event systems
• Data pipeline development with Spark, Airflow, or equivalent for batch processing and dataset creation
• AWS fluency: Lambda, EventBridge, SQS, ElastiCache, Aurora, S3 or equivalent cloud ML stack
• Experience with MLOps tooling: MLflow, Weights & Biases, or similar for experiment tracking, model registry, and monitoring

Preferred:

• Prior experience building out Machine Learning teams
• Contact center or telephony domain experience (Genesys, Amazon Connect, Twilio, Five9)
• Speech-to-text / ASR systems and handling transcription noise in downstream models
• Real-time streaming ML (as opposed to batch-only)
• Infrastructure-as-Code (Terraform) and CI/CD for ML systems
• Distributed training (e.g. DeepSpeed) for fine-tuning larger models

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.