MACHINE LEARNING ENGIENEER II (REMOTE)

The Home Depot; Atlanta (GA); On-site; USD 110,000 - 150,000; Full time

Job summary

The Home Depot in Atlanta is seeking a Machine Learning Engineer II to join a product team and contribute to software design, algorithm design, and the overall product lifecycle. You will pair daily with teammates to evolve ML solutions that users love, embedding AI components into software products.

You will collaborate with stakeholders across engineering, data science, and product teams to ensure requirements are met, and you will participate in performance tuning, monitoring, and education

Qualifications

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.
• 1 - 3 years of relevant work experience in ML/DS.
• Experience in Python and modern ML tools.
• Familiarity with data engineering and big data platforms.

Responsibilities

• Delivery and execution of ML-enabled solutions with product teams.
• Participates in design, development, and testing of ML applications.
• Provides production support and monitors ML systems and dashboards.

Skills

Python

Data engineering

BigQuery

Node.js

ReactJS

SQL

Git

ML algorithms

Statistics

TensorFlow

PyTorch

Jupyter

Pandas

Scikit-learn

GCP Vertex AI

Linux

CI/CD

REST

BigQuery ML

Education

High school diploma or GED

1 year of work experience in ML/DS

Tools

BigQuery

TensorFlow

PyTorch

Scikit-learn

Jupyter

Pandas

Job description

Position Purpose

The Machine Learning Engineer II is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.

Req196650

Position Purpose

The Machine Learning Engineer II is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. ML Engineers should be able to operate independently with minimum guidance from others, although will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.

Key Responsibilities

• 65% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Program configuration/modification and setup activities on large projects using HD approved methodology; 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
• 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

• 1 - 3 years of relevant work experience
• Experience in a modern scripting language (preferably Python)
• Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc
• Experience in modern web application framework such as Node.js
• Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3
• Experience in writing SQL queries against a relational database
• Experience in version control systems (preferable Git)
• Familiarity with algorithms such as 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 like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.
• Familiarity with Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML
• Familiarity with a Linux or Unix based environment
• Familiarity with a CI/CD toolchain
• Familiarity with REST and effective web service design
• Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security

Minimum Education

• The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education

• No additional education

Minimum Years Of Work Experience

• 1

Preferred Years Of Work Experience

• No additional years of experience

Minimum Leadership Experience

• None

Preferred Leadership Experience

• None

Certifications

• None

Competencies

• Global Perspective
• Manages Ambiguity
• Nimble Learning
• Self-Development
• Collaborates
• Cultivates Innovation
• Situational Adaptability
• Communicates Effectively
• Drives Results
• Interpersonal Savvy