Senior Software Engineer- Dev Ops/ML Ops (Remote)

Home Depot-posted 2 months ago
Full-time • Mid Level
Remote • Atlanta, GA
5,001-10,000 employees
Building Material and Garden Equipment and Supplies Dealers
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The Sr. Software Engineer is responsible for independently developing and consistently redesigning/refactoring a product to adapt to our customers and associates needs. As a Sr. 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 addition, Sr. Software Engineers may be involved in product and tool selection, configuration, security, resilience, performance tuning and production monitoring as well as mentoring less experienced engineers.

  • Design and Implement ML Pipelines: Build and maintain automated CI/CD pipelines for machine learning models, covering data preprocessing, model training, evaluation, and deployment.
  • Productionize Models: Work closely with data scientists to take models from experimentation to a production-ready state, often involving packaging models into microservices or APIs.
  • Manage Infrastructure: Provision and manage scalable and secure cloud infrastructure using tools like Docker and Kubernetes to support machine learning workloads.
  • Optimize Resources: Focus on optimizing the machine learning pipeline for efficiency, scalability, and cost-effectiveness.
  • Collaborate Cross-Functionally: Work with data scientists, ML engineers, software developers, and IT operations to streamline workflows and improve overall efficiency.
  • Troubleshoot and Support: Provide technical support and resolve production issues related to model performance, deployment, and infrastructure.
  • Must be eighteen years of age or older.
  • Must be legally permitted to work in the United States.
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
  • 2-4 years of relevant work experience in an MLOps, DevOps.
  • Strong programming skills in Python.
  • Experience with Infrastructure management tools, terraform, Jenkins, Python, Shell, Bash, Helm, Elastic Search, Github actions, Relational or noSQL database technology, cloud computing techniques, CI/CD tools, modern software design patterns, and their respective AI/ML services (e.g., AWS SageMaker, Google AI Platform).
  • Experience with security frameworks for user and services authorization and authentication.
  • Experience with creating and executing unit, functional, destructive and performance tests.
  • Experience with modern debugging and root cause analysis techniques.
  • Experience with version control system.
  • Experience with Kubernetes and cloud products.
  • Experience in networking traffic management.
  • Deep knowledge of containerization and orchestration tools, including Docker and Kubernetes.
  • Proven experience with CI/CD tools like Jenkins, GitLab CI, GitHub Actions, or Azure DevOps.
  • Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation is highly desirable.
  • Experience with ML experiment tracking and versioning tools like MLflow or DVC (Data Version Control) is a plus.
  • Solid understanding of software engineering best practices, including code testing, security, and documentation.
  • Excellent communication skills with the ability to effectively collaborate with both technical and non-technical teams.
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