Posted Aug 22, 2026

SR. Machine Learning Engineer, Enterprise AI Systems

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With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose:

The Sr Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Sr ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering.
Sr ML Engineers should be able to operate independently though will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.

Key Responsibilities:

Direct Manager/Direct Reports:

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Minimum Qualifications:

Preferred Qualifications:

  • 5+ years of experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related field, with a proven track record of building and deploying production-grade AI and machine learning solutions.
  • 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 that connect structured and unstructured data to enable AI and analytics use cases.
  • Experience developing scalable data pipelines, data products, and feedback loop architectures that support continuous model and agent improvement.
  • Proficiency in Python and modern AI/ML frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, Pandas, and related technologies.
  • Experience with cloud-native AI/ML platforms and infrastructure, preferably Google Cloud Platform (Vertex AI, BigQuery, BigQuery ML), including model deployment, monitoring, and MLOps practices.
  • Experience building and supporting AI infrastructure, including vector databases, model serving platforms, APIs, microservices, distributed systems, and high-availability architectures.
  • Strong understanding of software engineering best practices, including CI/CD, version control, automated testing, security, and performance optimization.
  • Experience working with large-scale structured and unstructured datasets, SQL, NoSQL, and modern data architecture patterns.
  • Strong communication, collaboration, and stakeholder management skills with the ability to influence technical decisions across engineering, data, analytics, and product teams.
  • Demonstrated ability to thrive in ambiguous environments, rapidly learn emerging technologies, solve complex problems, and drive innovation in a fast-paced organization.

Minimum Education:

Preferred Education:

Minimum Years of Work Experience:

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Minimum Leadership Experience:

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Certifications:

Competencies:

For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:

The pay range for this position is between $100,000.00 - $180,000.00

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