Staff Machine Learning Engineer (Remote)

GEORGIA - VIRTUAL - GA01

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose:

The Staff Software Engineer is responsible for leading a team of engineers building and designing a product that our customers and associates love. As a Staff Software Engineer, you will be part of a dynamic team with engineers of all experience levels who help each other build and grow technical and leadership skills while creating, deploying, and supporting production applications. In this role, you will also provide technical leadership on machine learning systems, including model development, production deployment, monitoring, and lifecycle management of ML solutions operating at scale. In addition, Staff Software Engineers will assist in product and tool selection, configuration, security, resilience, performance tuning and production monitoring.

Staff Software Engineers contribute to foundational code elements that can be reused as well as architectural diagrams and other product-related documentation. You will help define best practices for building reliable, explainable, and maintainable ML systems that integrate seamlessly with broader software platforms.

As a Staff Software Engineer, you will be a core player on the product team and are expected to build and grow the skillsets of the more junior Engineers.

Key Responsibilities:

45% Delivery and Execution - 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
15% Learning - 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
20% Strategy and Planning - 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
20% Support and Enablement - 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

Direct Manager/Direct Reports:

This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager
This Position has 0 Direct Reports

Travel Requirements:

Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:

Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

Must be eighteen years of age or older.
Must be legally permitted to work in the United States.

Preferred Qualifications:

3 - 6 years of relevant work experience
Strong experience designing, training, evaluating, and deploying machine learning models in production environments, including batch and real-time inference systems
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 to basic statistics and regression algorithms
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. - and experience integrating them into scalable software systems
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 (preferable Git)
Experience in a Linux or Unix based environment
Experience in a CI/CD toolchain
Experience in REST and effective web service design
Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
Experience in cloud computing platform and associated automation patterns and machine learning services they provide
Experience in defensive coding practices and patterns for high Availability
Experience in A/B testing and effective REST design for scalable web services architecture
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer