Software Engineer Manager, Machine Learning (Remote)

The Home Depot

4d•Remote

About The Position

With a career at The Home Depot, you can be yourself and also be part of something bigger. Position Purpose: As a Software Engineer Manager, you will be given a chance to contribute to the machine learning platforms and products we create and help grow the next generation of engineering talent.

Requirements

Must be eighteen years of age or older.
Must be legally permitted to work in the United States.
Mastery of an object oriented programming language (preferably Java)
Must be legally permitted to work in the United States

Nice To Haves

Experience with algorithms such as clustering, forecasting, anomaly detection, and neural networks.
Experience with basic statistics and regression algorithms
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, Scikit-learn, tensorflow, pytorch, etc.
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, etc
Experience in a modern scripting language (preferably Python)
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)
Experience in a Linux or Unix based environment
Experience in a CI/CD toolchain
Experience in REST and effective web service design
Experience with building AI Agents and Agentic Applications using frameworks like LangChain
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security
Familiarity with NoSQL databases
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.

Responsibilities

Delivery & Execution: Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions
Documents, reviews and ensures that all quality and change control standards are met
Writes custom code or scripts to automate infrastructure, monitoring services, and test cases
Works with vendors and partners for the successful implementation of critical tooling and platforms
Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment
Evaluates new technologies for adoption across the enterprise
Participates in and leads review board sessions to drive consistency across the enterprise
Fills in on product teams for engineers who are out of the office
Support & Enablement: Fields questions from engineers, 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
Acts as a technical escalation point for the engineers on the team
People: Provides leadership, mentoring, and coaching to Software Engineers
Attracts, retains, and develops top talent to build a world class Software Engineering Team
Conducts annual and mid-year reviews by reviewing individual development plans and team feedback
Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests
Acts as a proponent of modern software development practices
Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams
Participates in and contributes to learning activities around modern software design and development core practices (communities of practice)
Learning: Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations
Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems