SR. Machine Learning Engineer, Enterprise AI Systems
The Home Depot
- Georgia, Georgia, United States
- Remote
- $100,000 - $180,000 a year
- Posted Aug 13, 2026
Job description
About the role
Senior Machine Learning Engineer on an enterprise AI systems product team, responsible for designing, building, deploying, and monitoring production‑grade AI/ML solutions, collaborating with UX, engineering, and product management, and supporting the full product lifecycle.
About the company
The Home Depot is a leading retail company operating a vast network of home improvement stores, offering careers where employees can be themselves and contribute to a larger mission.
Requirements
- Must be at least 18 years old and legally authorized to work in the United States
- Minimum 2 years of work experience
- 5+ years of experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related field with proven production‑grade AI/ML deployments
- Experience designing and developing Agentic AI applications, LLM‑powered solutions, retrieval‑augmented generation (RAG) systems, and intelligent automation workflows
- Strong experience with knowledge graphs, graph engineering, network analysis, semantic search, and building enterprise knowledge layers
- Experience developing scalable data pipelines, data products, and feedback loop architectures for continuous model/agent improvement
- Proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit‑learn, Pandas
- Experience with cloud‑native AI/ML platforms, preferably Google Cloud (Vertex AI, BigQuery, BigQuery ML), including model deployment, monitoring, and MLOps practices
- Experience building AI infrastructure: vector databases, model serving platforms, APIs, microservices, distributed systems, high‑availability architectures
- Strong understanding of software engineering best practices: CI/CD, version control, automated testing, security, performance optimization
- Experience with large‑scale structured and unstructured datasets, SQL, NoSQL, and modern data architecture patterns
- Strong communication, collaboration, and stakeholder management skills; ability to influence technical decisions across engineering, data, analytics, and product teams
- Ability to thrive in ambiguous environments, rapidly learn emerging technologies, solve complex problems, and drive innovation