Senior Machine Learning, AI Platforms Engineer

The Home Depot

Machine Learning Engineer designing and maintaining AI-powered applications for Home Depot. Collaborating with cross-functional teams to ensure effective generative AI solutions.

Posted 6/26/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $100,000 - $180,000 per yearWebsite

Tech Stack

Tools & technologies

BigQueryCloudD3.jsGoogle Cloud PlatformJavaScriptNode.jsPythonReactSQL

About the role

Key responsibilities & impact

The Sr Machine Learning Engineer 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.
Sr 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.

Requirements

What you’ll need

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, CSS, 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.

Benefits

Comp & perks

health care benefits
401K
ESPP
paid time off
success sharing bonus

ATS Keywords

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Hard Skills & Tools

Pythonlarge language models (LLMs)prompt engineeringRetrieval-Augmented Generation (RAG)Google Cloud PlatformCI/CD pipelinesGPU accelerationSQLdata engineeringconversational AI

Soft Skills

collaborationindependencefeedbackcommunicationproblem-solvingadaptabilitycritical thinkingdocumentationorganizationstakeholder engagement