Senior AI Engineer & Data Scientist - Production ML

Home Depot; Atlanta (GA); On-site; USD 140,000 - 170,000; Full time

Job summary

The Home Depot is seeking a Sr. Data Scientist to build and scale agentic AI solutions that reason over enterprise data and orchestrate core data science models into production workflows.

You will apply software engineering discipline to automate model lifecycles, embed observability and governance, and collaborate with engineering and business teams. You will lead efforts to develop reusable AI services, manage projects, mentor teammates, and push innovations in GenAI, retrieval systems, and

Qualifications

• Bachelor's degree or equivalent in a related field.
• 5+ years of experience in data science or ML/AI with production deployments.
• Experience developing GenAI/LLM-based or Agentic AI solutions.
• Strong software engineering skills in Python and SQL.
• Experience with MLOps/LLMOps/AIOps practices.

Responsibilities

• 35% Solution Development — design and build algorithms/models for large datasets; communicate insights to technical and business stakeholders; prepare updates and reports.
• 30% Project Management & Team Support — set goals, prioritize work, mentor junior staff, allocate workload and resources.
• 20% Business Collaboration — translate analytics to business impact, build trust with internal customers, educate teams on advanced analytics.
• 15% Technical Exploration & Development — explore new AI architectures, codify reusable data products, document patterns and best practices.

Skills

Python

SQL

Docker/Kubernetes

MLOps

LLMOps

AIOps

Agentic AI

Retrieval systems

DevOps collaboration

Cloud deployment

Education

Bachelor's degree or equivalent

Tools

GCP

CI/CD tooling

Observability tooling

Job description

The Home Depot is seeking a Sr. Data Scientist to build and scale agentic AI solutions that reason over enterprise data and orchestrate core data science models into production workflows.

You will apply software engineering discipline to automate model lifecycles, embed observability and governance, and collaborate with engineering and business teams. You will lead efforts to develop reusable AI services, manage projects, mentor teammates, and push innovations in GenAI, retrieval systems, and