Applied Machine Learning Scientist - AI Agents

Grainger Businesses • Lake Forest, IL

1d • $102,300 - $188,100 • Remote

About The Position

We’re looking for an Applied Machine Learning Scientist to help shape the future of intelligent, customer-centered solutions within our Sales Hub or Customer Service ecosystem. As an Applied Machine Learning Scientist, you’ll partner closely with Product and Engineering teams to design, develop, and deploy ML-powered systems that strengthen Grainger’s customer relationships. This role is ideal for someone with foundational AI/ML experience who’s eager to work on real-world GenAI applications, including document intelligence, voice-based systems, retrieval-augmented generation (RAG), and agentic AI solutions. You will report to Sr Manager, Applied Machine Learning and although a Chicago based position is preferred (8 days a month in office), we will consider highly qualified remote candidates who can visit the Chicago office for initial onboarding and quarterly meetings.

Requirements

• A Bachelor's degree in applied mathematics, Physics, Engineering, Computer Science, Electrical Engineering, Economics, or 2 years of related industry work experience
• 1 year minimum of industry experience in Machine Learning/ GenAi
• Experience with deep learning frameworks such as PyTorch, Tensorflow, Huggingface
• Experience working with Generative AI or ML solutions such as finetuning, training, testing, validating.
• Experience deploying ML models using containerization and container orchestration technologies such as Docker and Kubernetes
• Ability to effectively communicate technical solutions to technical and business audiences, both verbally and in writing
• Experience with cloud providers such as AWS and Azure

Nice To Haves

• Advanced degree (PhD or Master’s) in Applied Mathematics, Physics, Engineering, Computer Science, Electrical Engineering, Economics, or related fields.
• Experience model quantization and deployment on model servers such as Triton
• Experience managing end-to-end software development life cycle (version control, CICD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support, etc.)
• Familiarity with machine learning libraries like LangChain, LlamaIndex, Autogen or Crew.ai
• Experience deploying models into the cloud with tooling like Docker & Kubernetes

Responsibilities

• Design and Build: Develop scalable, high-performance ML components that power end-to-end generative and agentic workflows—such as knowledge curation, search, context management, and workflow orchestration.
• Apply Advanced Techniques: Work with Deep Learning, LLMs, VLMs, fine-tuning, and prompt optimization to enhance how Grainger manages and leverages complex content.
• Collaborate Cross-Functionally: Partner with Product, Engineering, and Business teams to align ML initiatives with Grainger’s customer-focused strategy.
• Drive ML Excellence: Contribute to best practices in model deployment, testing, CI/CD, and monitoring, ensuring robust, maintainable, and ethical AI solutions.
• Own the Lifecycle: Support the full ML lifecycle—from prototyping and deployment to evaluation, monitoring, and iterative improvement.
• Learn and Evolve: Stay current with emerging ML trends and research, introducing innovative techniques to improve performance and impact.

Benefits

• Medical, dental, vision, and life insurance plans with coverage starting on day one of employment
• 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)
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree