Senior Machine Learning Engineer, Enterprise AI Systems

Job not on LinkedIn

🔥 0 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

The Home Depot

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1978

🏗️ Construction

📦 Logistics

🛒 Retail

💰 Debt Financing on 2007-07

Construction • Logistics • Retail

The Home Depot is a leading home improvement retailer, offering a wide range of building materials, home improvement products, lawn and garden products, and related services. The company operates both physical stores and an online platform, providing comprehensive solutions for DIY enthusiasts, professional contractors, and homeowners. The Home Depot is committed to diversity, equity, and inclusion, providing employment opportunities and benefits to a diverse workforce. Additionally, the company places a high emphasis on customer service and associate engagement to maintain its position as a trusted leader in the home improvement industry.

📋 Description

• Join a product team and contribute to software design, algorithm design, and the overall product lifecycle • Design and implement AI/ML algorithms embedded directly into software products • Interface with business stakeholders, technology infrastructure teams, and development teams to meet business requirements • Perform performance tuning, testing, product monitoring, and data engineering • Create, support, and deploy production applications • Review submitted code and provide feedback based on best practices • Collaborate and pair 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 • Ensure developer-ready, understandable, and testable user stories • Write code or scripts to automate infrastructure, monitoring services, test cases, and destructive testing • Configure commercial off-the-shelf solutions to align with business needs • Create dashboards, logging, alerting, and proactive responses • Field questions from product and support teams and encourage collaboration • Provide application support for production software • Monitor production Service Level Objectives • Review production performance and capacity across code, infrastructure, data, message processing, and prediction quality

🎯 Requirements

• 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 2 years of work experience • Preferred: 5+ years of experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related field • Experience designing Agentic AI applications, LLM-powered solutions, RAG systems, and intelligent automation workflows • Experience with knowledge graphs, graph engineering, network analysis, semantic search, and enterprise knowledge layers • Experience developing scalable data pipelines, data products, and feedback loop architectures • Proficiency in Python, PyTorch, TensorFlow, Scikit-learn, Pandas, and related technologies • Experience with cloud-native AI/ML platforms, preferably Google Cloud Platform, Vertex AI, BigQuery, and BigQuery ML • Experience with model deployment, monitoring, and MLOps practices • Experience building and supporting vector databases, model serving platforms, APIs, microservices, distributed systems, and high-availability architectures • Strong understanding of CI/CD, version control, automated testing, security, and performance optimization • Experience with large-scale structured and unstructured datasets, SQL, NoSQL, and modern data architecture patterns • Strong communication, collaboration, and stakeholder management skills • Ability to influence technical decisions across engineering, data, analytics, and product teams • Ability to thrive in ambiguous environments, learn emerging technologies, solve complex problems, and drive innovation

🏖️ Benefits

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