Senior Machine Learning Engineer- Generative AI (REMOTE)

The Home Depot

Atlanta (GA)

Remote

USD 140,000 - 210,000

Full time

14 days+

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Job summary

The Home Depot is seeking a Senior Generative AI Engineer to design, build, and scale AI-powered applications leveraging LLMs and other generative models. You will collaborate with product, software, and data teams to deliver secure, reliable AI features and implement RAG pipelines, model integration, and monitoring in production.

You will work with domain data, improve prompts, and help create documentation for AI solutions while aligning with responsible AI practices and security requirements.

Qualifications

Eighteen years or older and eligible to work in the U.S.
2+ years of relevant work experience in ML/AI roles per the ad.
Strong Python and modern AI development frameworks, including LLMs.
Experience with prompt engineering, evaluation, and optimization.
Experience integrating AI models via APIs (Google/OpenAI/Anthropic).
Familiarity with GenAI frameworks and RAG pipelines.
Knowledge of vector databases and Vertex AI Search.

Responsibilities

Collaborate cross-functionally to design and deliver scalable ML solutions.
Develop and maintain AI-powered applications using LLMs and generative models.
Build and optimize RAG pipelines, prompts, and AI workflows.
Monitor production AI services and ensure reliability, security, and compliance.

Skills

Python

LLMs

Prompt engineering

APIs integration

CI/CD

GPU acceleration

SQL

Node.js / React

Data engineering

Monitoring & observability

Education

High school diploma or GED

No additional education

Tools

Google Cloud Platform

Vertex AI

BigQuery

Vector databases

REST APIs

CI/CD tooling

Containerization (Docker)

Monitoring tools

Jupyter / Python notebooks

Data pipelines

Job description

Position Purpose:

The Sr Machine Learning Engineer is responsible for designing, building, integrating, optimizing, and maintaining AI-powered applications that leverage generative models and the 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.

Key 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

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:

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