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

Position Purpose:

The Staff 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. Staff 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.
Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design

Required skills

• Experience: 6+ years (Senior) or 8+ years (Lead) of experience in AI, Machine Learning Engineering, or Software Engineering with strong Python development skills and modern software engineering practices.
• AI Delivery: Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems.
• AI Foundations: Deep understanding of AI/ML foundations, including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases.
• Orchestration & Integration: Experience developing orchestration layers (task execution, routing, planning, workflows) and seamlessly integrating AI solutions with enterprise platforms, APIs, and business systems.
• Infrastructure & MLOps: Expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (e.g., Terraform), and AI pipeline design, with hands-on implementation of MLOps/LLMOps best practices (CI/CD, automated testing, model versioning and registries, governance, compliance, and security) across the full AI/agent lifecycle.
• AIOps & Deployment Reliability: Experience building automated CI/CD pipelines for AI/agentic systems, implementing progressive rollout strategies (canary, blue-green, and shadow deployments) with automated rollback, and establishing end-to-end observability (logging, metrics, distributed tracing, and automated alerting) across models, agents, and orchestration layers to ensure production reliability, performance, and cost/token efficiency at scale.
• Optimization & Debugging: Demonstrated ability to optimize complex AI systems for performance, reliability, scalability, latency, cost efficiency, and token use, as well as debugging operational failure modes.
• Execution & Collaboration: Excellent cross-functional communication and collaboration skills, with a proven ability to take AI solutions from concept to production in complex enterprise environments.

Key Responsibilities:

• 45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
• 15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate
• 20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses
• 20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Direct Manager/Direct Reports:

• This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager
• This Position has 0 Direct Reports

Travel Requirements:

• Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications:

• Tools & Frameworks: Hands-on experience with Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, AutoGen, or similar orchestration tools and frameworks.
• AI Infrastructure & Platform Tooling: Hands-on experience with infrastructure-as-code (e.g., Terraform), Kubernetes/GKE for container orchestration, GPU/accelerator provisioning and autoscaling, model registries, feature stores, and vector database operations at production scale.
• Full‑stack skills: Node.js/React/REST, API design, performance optimization, Linux, Git, modern deployment toolchain.
• Industry Context: Background in retail, supply chain, manufacturing, eCommerce, logistics, or finance where Applied ML is mature.
• Guardrails & Reliability: Knowledge and experience in establishing Responsible AI, evaluation frameworks, reliability engineering, and AI governance guardrails.
• Leadership & Innovation: A proven track record of driving innovation, delivering measurable business impact, mentoring engineering teams, and establishing AI engineering standards and best practices.
• Master’s or bachelor’s in computer science, Artificial Intelligence, Machine Learning, or a related technical discipline.

Minimum Education:

• The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education:

• No additional education

Minimum Years of Work Experience:

• 3

Preferred Years of Work Experience:

• No additional years of experience

Minimum Leadership Experience:

• None

Preferred Leadership Experience:

• None

Certifications:

• None

Competencies:

• Global Perspective
• Manages Ambiguity
• Nimble Learning
• Self-Development
• Collaborates
• Cultivates Innovation
• Situational Adaptability
• Communicates Effectively
• Drives Results
• Interpersonal Savvy

Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus.  For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.

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 $120,000.00 - $190,000.00