Lowe’s is hiring a Software Engineer – ML in Charlotte, North Carolina, offering an exciting opportunity to work on machine learning-driven software solutions at one of the leading home improvement retailers in the U.S. This role is ideal for engineers who enjoy building scalable applications, working with ML technologies, and solving real-world business problems through data and software.
Job Overview
| Field | Details |
|---|---|
| Company Name | Lowe’s |
| Role | Software Engineer – ML |
| Qualification | Bachelor’s degree in Computer Science, Engineering, or a related field; relevant software engineering and machine learning experience |
| Job Location | Charlotte, NC, USA |
| Salary | $135,000–$180,000 per year |
| Work Type | On-site / Hybrid |
| Job Type | Full-Time |
| Job Level | Entry Level |
| Industry | Retail / Technology / Home Improvement |
Job Description
- Build and maintain scalable data ingestion, transformation, feature engineering, and post-processing pipelines to support model training, inference, analytics, and reporting.
- Collaborate with Data Scientists, Product, and Business teams to translate business requirements into scalable AI/ML solutions and production-ready data pipelines.
- Design, develop, deploy, and maintain end-to-end ML systems, including model packaging, registration, versioning, deployment, and serving using platforms such as MLflow, Vertex AI, Kubeflow, or similar MLOps tools.
- Build and optimize batch and real-time inference pipelines for performance, scalability, reliability, and cost efficiency across cloud and on-premises environments.
- Implement and maintain CI/CD pipelines and workflow orchestration for AI/ML models and data pipelines using DevOps and MLOps best practices.
- Design and implement monitoring frameworks to track model performance, data quality, data drift, model drift, and production system health.
- Build reusable libraries, utilities, and platform components that improve engineering productivity and standardize ML development across teams.
- Develop production-quality software components following software engineering best practices, ensuring solutions are scalable, testable, maintainable, and efficient.
- Perform root cause analysis, troubleshoot production issues, and participate in code reviews to improve code quality, reliability, and operational excellence.
- Ensure AI/ML solutions comply with security, governance, privacy, and organizational standards throughout the development lifecycle.
- Champion engineering best practices to continuously improve the reliability, scalability, maintainability, and operational efficiency of AI/ML platforms and pipelines.
Skill Set requirements: Apache Airflow, Cloud Composer, GCP cloud experience, Big Query, Trino/Presto. Experience working on Data Quality/Integrity theme, Tools like Great Expectations. Domain experience on retail forecasting or any other business forecast predictions/time series forecasting.
Minimum Qualifications
- Bachelor’s degree in computer science, computer information systems, or related field or equivalent years of experience in lieu of education requirement, if applicable
- 2 years of experience in software development or a related field
- 2 years of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC) through iterative agile development
- 2 years experience working with any of the following: frontend technologies (user interface/user experience), middleware (microservices and application programming interfaces), database technologies, or DevOps
Preferred Skills/Education
- Minimum 2 years of experience developing production software and AI/ML applications with large datasets.
- 2 years of experience writing technical documentation in a software environment and developing and implementing business systems within an organization
- 1+ year of experience delivering solutions using Agile methodologies and Software Development Life Cycle (SDLC)
- Must be well-versed with ML system deployment/release process with live inference, batch inference, and model versioning.
- Experience with Data Engineering and building data/ML pipelines.
- Hands-on experience building robust, reliable, and scalable AI/ML pipelines.
- Experience with MLOps tools such as MLflow, Kubeflow, or Vertex AI.
- Foundational understanding of ML models.
- Strong understanding of cloud platforms (GCP, AWS, or Azure).
- Strong understanding of software engineering best practices, including code reviews, testing, debugging, and writing maintainable, production-quality code.
- Experience managing model registry and implementing versioning best practices.
- Model serving frameworks. SQL, Python, PySpark. Big Data technologies (Hadoop ecosystem or cloud-native equivalents), Analytics databases, visualization tools, CI/CD and Git.
Selection Process
- Application submission and resume screening
- Recruiter screening
- Technical interview
- Coding and/or machine learning assessment
- Hiring manager interview
- Team/technical discussions
- Final interview and offer
How to Apply
- Review the Software Engineer – ML job requirements.
- Prepare an updated resume highlighting software engineering and ML experience.
- Submit your application through Lowe’s official careers portal or the applicable job listing.
- Complete any required assessments or technical interviews.
- Attend recruiter and hiring manager interviews.
- If selected, complete the final hiring and onboarding process.
