Staff Machine Learning Engineer

The Home Depot

Staff Machine Learning Engineer leading machine learning projects at Home Depot. Collaborating with engineering teams to deliver scalable ML solutions and support production applications.

Posted 5/20/2026full-timeRemote • 🇺🇸 United StatesLead💰 $120,000 - $190,000 per yearWebsite

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformLinuxPandasPythonPyTorchScikit-LearnSQLTensorflowUnix

About the role

Key responsibilities & impact

Collaborates and pairs with other product team members to create secure, reliable, scalable machine learning solutions
Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable
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
Participates in learning activities around modern software design, machine learning, and development core practices
Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives
Leads the evaluation development and recommendation of specific technology products and platforms
Monitors tools and participates in conversations to encourage collaboration across product teams
Provides application support for software running in production
Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Requirements

What you’ll need

3 - 6 years of relevant work experience
Strong experience designing, training, evaluating, and deploying machine learning models in production environments
Experience with ML lifecycle management, including feature engineering, model versioning, experimentation, validation, and monitoring for data drift and model performance degradation
Experience building and operating ML pipelines using cloud-native services, data platforms, and CI/CD practices for reproducible and reliable model deployment
Strong understanding of applied statistics, model evaluation metrics, and tradeoffs between model accuracy, interpretability, latency, and operational cost
Experience with algorithms such as clustering, forecasting, anomaly detection, and neural networks.
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embedding generation and utilization
Experience in training machine learning models with extremely large datasets
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, TensorFlow, PyTorch, etc.
Experience in Google Cloud Platform and AI/ML-related components such as Vertex AI, BigQueryML, and AutoML
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 in writing SQL queries against a relational database
Experience in version control systems (preferably Git)
Experience in a Linux or Unix-based environment
Experience in a CI/CD toolchain
Experience in production systems design, including High Availability, Disaster Recovery, Performance, Efficiency, and Security
Experience in cloud computing platforms and associated automation patterns

Benefits

Comp & perks

Competitive salary
Health insurance
Paid time off
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningmodel trainingmodel evaluationfeature engineeringdata analysisNLPconvolutional neural networksSQLPythonCI/CD

Soft Skills

collaborationcommunicationproblem-solvingleadershipproactiveanalytical thinkingadaptabilityorganizational skillscritical thinkingcreativity