[Hiring] Senior Machine Learning Engineer @The Home Depot

Role Description

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.

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.

Qualifications

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

Requirements

• 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.
• 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

• Typically requires overnight travel 5% to 20% of the time.
• Most of the time is spent sitting in a comfortable position with frequent opportunities to move about.
• Located in a comfortable indoor area with infrequent and non-objectionable unpleasant conditions.

Company Description

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