The Home DepotRemote
Staff Machine Learning Engineer – Generative AI (Remote)
United States of America
Full Time
3 hours ago
No H1B
Key skills
PythonGenerative AI applicationsLarge language modelsRetrieval-Augmented GenerationAI model integrationVector databasesCI/CD pipelinesGoogle Cloud PlatformData engineering practicesPrompt engineeringConversational AI systemsMonitoring AI systemsSQL queriesMachine learning techniquesData Analysis toolsCloud computing familiarityDefensive coding practicesA/B testingJavaScriptSQLAIMachine LearningMLNLPGenerative AIGenAILarge Language ModelsOpenAIAnthropicRAGPyTorchTensorFlowscikit-learnPandasJupyterData EngineeringBigQueryNode.jsGoogle CloudVertex AICI/CDProduct ManagementA/B TestingCollaboration
About this role
The Home Depot is seeking a Staff Machine Learning Engineer to join cross-functional teams to build innovative Generative AI application experiences. This role involves collaborating with product, design, and engineering teams to develop scalable AI services and support the product lifecycle.
Responsibilities:
- Collaborates and pairs with other product team members (UX, engineering, and product management) 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 (communities of practice)
- Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
- Attends conferences and learns how to apply new innovations and technologies where appropriate
- 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 to provide cost-effective solutions that meet business and technology requirements
- Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products
- Proactively creates and maintains tools for monitoring and support
- Participates in project planning and management across multiple efforts
- Develops formal training courses
- Fields questions from other product teams or support teams
- Monitors tools and participates in conversations to encourage collaboration across product teams
- Provides application support for software running in production
- Proactively monitors production Service Level Objectives for products
- Proactively reviews the Performance and Capacity of all aspects of production: 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
- 3 years of relevant work experience
- 5 - 7 years of relevant 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 with building conversational AI systems, or AI assistants
- Experience with responsible AI practices including bias mitigation and safety guardrails
- Experience working with graph databases, knowledge ingestion pipelines, and data mesh architectures to enable scalable, connected, and queryable AI knowledge systems
- 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 related components such as Vertex AI, BigQueryML, and 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 with GPU acceleration (i.e. CUDA and cuDNN)
- Experience in a front-end technology and framework such as Node.js, HTML, CCS, JavaScript, ReactJS, D3
- Experience in writing SQL queries against a relational database
- Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings 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
- Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
- Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide
- Familiarity with defensive coding practices and patterns for high Availability
- Familiarity with A/B testing and effective 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
- Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer