Machine Learning Engineer II

The Home Depot

. Join a product team and contribute to software design, algorithm design, and the overall product lifecycle .

Posted 11/3/2026full-timeRemote • United StatesJunior💰 $90,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI/ML algorithm design and implementation, data engineering practices, and modern web application frameworks. Proficient in collaborating with cross-functional teams to deliver scalable and reliable software solutions while ensuring quality and performance standards are met.

Highest-signal resume keywords

Python ProgrammingData Engineering PracticesMachine Learning ToolsWeb Application FrameworksSQL Query Writing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML Algorithm DesignData EngineeringSQLPythonNode.jsHTMLCSSJavaScriptReactJSD3

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

BigQueryGitJupyter NotebooksTensorFlowPyTorchGoogle Cloud PlatformCI/CD Toolchains

Industry Keywords

Machine LearningData AnalysisStatisticsProduction Systems DesignHigh Availability

Tech Stack

Tools & technologies

BigQueryCloudD3.jsGoogle Cloud PlatformJavaScriptLinuxNode.jsPandasPythonPyTorchReactScikit-LearnSQLTensorflowUnix

About the role

Key responsibilities & impact

Join a product team and contribute to software design, algorithm design, and the overall product lifecycle
Pair daily with product team members while working through user stories and supporting evolving products
Design and implement AI/ML algorithms embedded directly into software products
Perform integration, design, and development using Home Depot process techniques
Interface with business stakeholders, technology infrastructure teams, and development teams to meet business requirements
Perform performance tuning, testing, and product monitoring
Conduct customer outreach, design ML educational materials, and perform data engineering
Create, support, and deploy production applications
Review submitted code and provide feedback based on best practices
Collaborate with UX, engineering, and product management to create secure, reliable, scalable machine learning solutions
Document, review, and ensure quality and change control standards are met
Create developer-ready, understandable, and testable user stories with the product team
Write custom code or scripts to automate infrastructure, monitoring services, and test cases
Conduct destructive testing to ensure production resiliency
Configure and modify programs and set up large projects using approved methodology
Configure commercial off-the-shelf solutions to align with evolving business needs
Create dashboards, logging, alerting, and responses to proactively capture and address issues
Participate in learning activities and communities of practice around modern software design, machine learning, and development
Field questions from product and support teams
Monitor tools and encourage collaboration across product teams
Provide application support for production software
Monitor production Service Level Objectives
Review performance and capacity across code, infrastructure, data, message processing, and prediction quality
Report to a Software Engineer Manager or Senior Software Engineer Manager; no direct reports

Requirements

What you’ll need

Must be eighteen years of age or older
Must be legally permitted to work in the United States
Minimum education: high school diploma and/or GED
Minimum 1 year of work experience
Experience in a modern scripting language, preferably Python
Experience in effective data engineering practices and big data platforms such as BigQuery and Data Store
Experience with modern web application frameworks such as Node.js
Experience with front-end technologies and frameworks such as HTML, CCS, JavaScript, ReactJS, and D3
Experience writing SQL queries against a relational database
Experience with version control systems, preferably Git
Familiarity with clustering, forecasting, anomaly detection, and neural networks
Familiarity with basic statistics and regression algorithms
Familiarity with advanced statistics such as Bayesian statistics
Familiarity with data analysis and machine learning tools and libraries such as Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, TensorFlow, and PyTorch
Familiarity with Google Cloud Platform and AI/ML components such as Vertex AI, BigQueryML, and AutoML
Familiarity with Linux or Unix-based environments
Familiarity with CI/CD toolchains
Familiarity with REST and effective web service design
Familiarity with production systems design, including high availability, disaster recovery, performance, efficiency, and security

Benefits

Comp & perks

Remote/Virtual work arrangement
Overnight travel typically limited to 5% to 20% of the time