MACHINE LEARNING ENGINEER II (REMOTE)

The Home Depot is a leading home improvement retailer, and they are seeking a Machine Learning Engineer II to join their product team. This role involves collaborating on software and algorithm design, contributing to the product lifecycle, and ensuring that machine learning solutions meet business requirements.

Responsibilities:

• 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
• Seniority
• Machine Learning Engineer II
• Summary
• The Home Depot is a leading home improvement retailer, and they are seeking a Machine Learning Engineer II to join their product team. This role involves collaborating on software and algorithm design, contributing to the product lifecycle, and ensuring that machine learning solutions meet business requirements

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
• 1 year of work experience
• 2+ years of experience in Machine Learning, Data Science, Software Engineering, or a related field
• Experience developing, training, and deploying machine learning models in production environments
• Hands-on experience with ML frameworks and tools such as Python, Scikit-learn, TensorFlow, PyTorch, Pandas, and Jupyter Notebooks
• Experience with feature engineering, model evaluation, experimentation, and monitoring
• Knowledge of machine learning techniques including classification, regression, clustering, forecasting, and anomaly detection
• Experience working with cloud-based ML platforms, preferably Google Cloud Platform (GCP), Vertex AI, and BigQuery
• Strong SQL and Python skills with experience working on large datasets
• Familiarity with MLOps, CI/CD pipelines, Git, and Linux/Unix environments
• Experience building and consuming REST APIs and integrating ML solutions into applications
• Understanding of software engineering best practices, scalability, reliability, and system performance
• Exposure to deep learning, NLP, Generative AI, or LLM-based solutions is a plus
• Experience with A/B testing and data-driven decision making