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Machine Learning Engineer II – Generative AI (Remote)

Roles & Responsibilities

  • 1–3 years of relevant work experience in Generative AI, Machine Learning, or AI application development
  • Experience in Python and modern AI development frameworks
  • Experience building Generative AI applications using large language models (LLMs)
  • Experience with prompt engineering, prompt optimization, and prompt evaluation techniques

Requirements:

  • Delivery and Execution: Collaborates with UX, engineering, and product management to create secure, reliable, and scalable machine learning solutions; documents and reviews quality and change-control standards; ensures user stories are developer-ready, easy to understand, and testable
  • Automation and resiliency: Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; performs destructive testing to ensure resiliency in production; handles program configuration/modification on large projects using Home Depot approved methodologies
  • Integration and deployment: Configures commercial off-the-shelf solutions to align with evolving business needs; integrates AI models via APIs from platforms such as Google, OpenAI, or Anthropic; develops and maintains CI/CD pipelines and monitoring for reliable AI deployments
  • Monitoring and enablement: Creates dashboards, logging, alerting, and responses; monitors production SLAs and evaluates performance and capacity of production components; provides application support and cross-team collaboration

Job description

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

Position Purpose:

The Machine Learning Engineer II is responsible for designing, building, integrating, optimizing, and maintaining AI-powered applications that leverage generative models and overall product lifecycle for a product that our users love. Generative AI Engineers are expected to collaborate closely with teammates as they develop and deliver user stories while supporting AI-powered products as they evolve. Generative AI Engineers may design and implement applications using large language models (LLMs) and other generative models to embed intelligent capabilities directly into software products. Activities may include prompt engineering, model integration, building Retrieval-Augmented Generation (RAG) pipelines, and developing scalable AI services. The role may interact with business stakeholders, infrastructure teams, and development teams to ensure business requirements are effectively addressed through generative AI solutions. The role may also support evaluation, performance optimization, testing, and monitoring of AI systems in production. Additional responsibilities may include working with domain data, improving prompts and AI workflows, and creating documentation or enablement materials for generative AI solutions.

Generative AI Engineers should be able to work independently with minimal guidance, while collaborating with cross-functional teams of varying skill levels to design, deploy, and maintain production AI applications. This role may review submitted code and prompt implementations, providing feedback and improvements based on engineering and responsible AI best practices.


Key Responsibilities:

  • 65% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Program configuration/modification and setup activities on large projects using HD approved methodology; 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
  • 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:

  • 1–3 years of relevant work experience in Generative AI, Machine Learning, or AI application development
    Experience in Python and modern AI development frameworks
    Experience building Generative AI applications using large language models (LLMs)
    Experience with prompt engineering, prompt optimization, and prompt evaluation techniques
    Experience integrating AI models through APIs from platforms such as Google, OpenAI or Anthropic
    Experience with GenAI frameworks such as Google Agent Development Kit (ADK)
    Experience implementing Retrieval-Augmented Generation (RAG) pipelines using vector databases
    Experience working with vector databases such as google Vertex AI Search
    Familiarity with building conversational AI systems, or AI assistants
    Familiarity with responsible AI practices including bias mitigation and safety guardrails
    Familiarity with REST APIs, microservices architecture, and scalable AI system deployment
    Familiarity implementing CI/CD pipelines, monitoring, and automated workflows for reliable AI model deployment and lifecycle management.
    Familiarity with monitoring, evaluation, and optimization of production AI systems


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:

  • 1


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 $90,000 - $170,000

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