Senior Machine Learning Engineer- Generative AI (REMOTE)

The Home Depot is seeking a Senior Machine Learning Engineer specializing in Generative AI to design, build, integrate, optimize, and maintain AI-powered applications throughout the product lifecycle. The role focuses on developing production AI solutions using large language models and other generative models, supporting cross-functional delivery, monitoring system performance, and enabling reliable, scalable, and responsible AI applications.

Responsibilities:

• 70% 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; 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
• 10% 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

Requirements:

• Must be eighteen years of age or older
• Must be legally permitted to work in the United States
• The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED
• 2
• 3 - 5 years of relevant work experience
• 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
• Experience with building conversational AI systems, or AI assistants
• Experience with responsible AI practices including bias mitigation and safety guardrails
• Experience working with graph databases, knowledge ingestion pipelines, and data mesh architectures to enable scalable, connected, and queryable AI knowledge systems
• Experience implementing CI/CD pipelines, monitoring, and automated workflows for reliable AI model deployment and lifecycle management
• Experience with monitoring, evaluation, and optimization of production AI systems
• Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)
• Experience with GPU acceleration (i.e. CUDA and cuDNN)
• Experience in a front-end technology and framework such as Node.js, HTML, CCS, JavaScript, ReactJS, D3
• Experience in writing SQL queries against a relational database
• Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
• Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide
• Familiarity with defensive coding practices and patterns for high Availability
• Familiarity with A/B testing and effective REST design for scalable web services architecture
• Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization
• No additional education
• No additional years of experience
• None