$100,000 – $250,000
Listed on The Home Depot’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role designs and deploys production AI systems using large language models and agentic workflows at scale. It suits experienced machine learning engineers and software architects who want to bridge AI research with enterprise reliability and business impact.
Our summary, not The Home Depot’s wording. The full posting is on their site.
Skills this role names
- CI/CD
- CrewAI
- Docker
- Embeddings
- Gemini
- Git
- Kubernetes
- LangGraph
- Linux
- LLMs (Large Language Models)
- MLOps
- Node.js
- Prompt Engineering
- Python
- React
- REST APIs
- Retrieval-Augmented Generation (RAG)
- Terraform
- Vector Databases
Log in to see which of these are already on your profile.
What they ask for
Required
- 6+ years in AI, Machine Learning Engineering, or Software Engineering
- Strong Python development and modern software engineering practices
- Proven production AI delivery with LLMs, SLMs, RAG, and multi-agent systems
- Deep understanding of AI/ML foundations including transformers, embeddings, and agentic reasoning
- Experience building orchestration layers and integrating AI with enterprise systems
- Cloud-native architecture expertise with Docker and Kubernetes
- Hands-on MLOps/LLMOps implementation across CI/CD, testing, versioning, governance
- Experience with automated CI/CD pipelines, progressive rollout strategies, and observability
- Ability to optimize AI systems for performance, reliability, scalability, and cost efficiency
- Cross-functional collaboration skills to deliver AI solutions in enterprise environments
Nice to have
- Hands-on experience with Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, or AutoGen
- Infrastructure-as-code, Kubernetes/GKE, GPU provisioning, model registries, feature stores
- Full-stack skills in Node.js, React, REST, API design, Linux, Git
- Background in retail, supply chain, manufacturing, eCommerce, logistics, or finance
- Knowledge of Responsible AI, evaluation frameworks, and AI governance
- Track record of driving innovation and mentoring teams
- Bachelor's or Master's in Computer Science, AI, Machine Learning, or related discipline