Senior Machine Learning Engineer – Generative AI

Job not on LinkedIn

🔥 14 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🗣️ LLM Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Design, build, integrate, optimize, and maintain AI-powered applications using generative models • Support the overall product lifecycle for generative AI products • Collaborate with UX, engineering, product management, business stakeholders, infrastructure teams, development teams, and support teams • Design and implement applications using large language models and other generative models • Perform prompt engineering, model integration, RAG pipeline development, and scalable AI service development • Evaluate, test, monitor, and optimize AI systems in production • Work with domain data and improve prompts and AI workflows • Create documentation and enablement materials for generative AI solutions • Work independently with minimal guidance while collaborating with cross-functional teams • Review code and prompt implementations and provide feedback based on engineering and responsible AI best practices • Document, review, and ensure quality and change control standards are met • Ensure user stories are developer-ready, understandable, and testable • Write custom code or scripts to automate infrastructure, monitoring services, and test cases • Perform destructive testing to ensure production resiliency • Configure commercial off-the-shelf solutions for evolving business needs • Create dashboards, logging, alerting, and proactive issue responses • Field questions from product and support teams • Provide application support for software running in production • 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 • Maintain no direct reports

🎯 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 • 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 building conversational AI systems or AI assistants • Experience with responsible AI practices, including bias mitigation and safety guardrails • Experience with graph databases, knowledge ingestion pipelines, and data mesh architectures • 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 components such as Vertex AI and BigQueryML • Experience with data engineering practices and big data platforms such as BigQuery and Data Store • Experience in a modern scripting language, preferably Python • Experience with GPU acceleration such as CUDA and cuDNN • Experience in front-end technologies and frameworks such as Node.js, HTML, CSS, JavaScript, ReactJS, and D3 • Experience 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 platforms, automation patterns, and machine learning services • Familiarity with defensive coding practices and patterns for high availability • Familiarity with A/B testing and 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

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