HD Supply

6 months ago

Senior Software Engineer- AI & Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Architect and manage production-grade MLOps deployment pipelines, connecting ML engineering with enterprise infrastructure. Own CI/CD and model lifecycle workflows (validation, packaging, testing, deployment, rollback), deploy containerized microservices on Kubernetes or managed cloud, and implement monitoring for performance, drift, and system health. Automate operational workflows with Airflow, document runbooks and incidents, and perform post-mortems to improve reliability.

Location: India

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Define MLOps pipeline architecture including version control, model validation, deployment, and rollback mechanisms.
•Build and maintain CI/CD pipelines for ML workflows, including model packaging, testing, and serving.
•Deploy containers and microservices to Kubernetes or managed cloud services and support production ML deployments (caching, load balancing, version rollback).
•Implement monitoring to track model performance, drift, and system health.
•Automate operational tasks such as deployments, scaling, canary releases, and job scheduling via Airflow; document playbooks and run incident post-mortems.

Key Requirements

•Bachelor’s or Master’s degree in computer science, software engineering, or related fields.
•4–7 years in ML/DevOps roles building CI/CD pipelines and deployment frameworks for ML applications.
•Experience implementing CI/CD pipelines for ML artifacts and model packaging, including deployment and rollback support.
•Proficiency with containerization (Docker), orchestration (Kubernetes / EKS / GKE), and Airflow/Prefect pipelines.
•Hands-on production ML deployment experience including monitoring, logging, and automated testing.

Experience:4-7 yearsMachine learningMLOpsDevOps

Education:

Skills:Problem-solvingRoot cause analysisDocumentation

Certifications:DevOpsKubernetesGCPMLOpsCloud-native technologies

Tech Stack:CI/CDJenkinsGitLab CIAzure DevOpsLinuxDockerKubernetesEKSGKEAirflowPrefectGoogle Cloud PlatformGCPVertex AIPrometheusGrafanaELK stackPythonBashMicroservices

Company Brief

HD Supply

Wholesale distributor of maintenance, repair and operations (MRO) products, providing building materials, construction supplies, and related services to contractors, property managers, and facility maintenance professionals across North America.

Industry: Wholesale & Distribution

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Unicorn (USD 1B+)

Funding: Private Equity Backed

Headquarters: Atlanta, United States

Website LinkedIn

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HD Supply

6 months ago

Senior Software Engineer- AI & Data

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: India

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Define MLOps pipeline architecture including version control, model validation, deployment, and rollback mechanisms.
•Build and maintain CI/CD pipelines for ML workflows, including model packaging, testing, and serving.
•Deploy containers and microservices to Kubernetes or managed cloud services and support production ML deployments (caching, load balancing, version rollback).
•Implement monitoring to track model performance, drift, and system health.
•Automate operational tasks such as deployments, scaling, canary releases, and job scheduling via Airflow; document playbooks and run incident post-mortems.

Key Requirements

•Bachelor’s or Master’s degree in computer science, software engineering, or related fields.
•4–7 years in ML/DevOps roles building CI/CD pipelines and deployment frameworks for ML applications.
•Experience implementing CI/CD pipelines for ML artifacts and model packaging, including deployment and rollback support.
•Proficiency with containerization (Docker), orchestration (Kubernetes / EKS / GKE), and Airflow/Prefect pipelines.
•Hands-on production ML deployment experience including monitoring, logging, and automated testing.

Experience:4-7 yearsMachine learningMLOpsDevOps

Education:

Skills:Problem-solvingRoot cause analysisDocumentation

Certifications:DevOpsKubernetesGCPMLOpsCloud-native technologies

Tech Stack:CI/CDJenkinsGitLab CIAzure DevOpsLinuxDockerKubernetesEKSGKEAirflowPrefectGoogle Cloud PlatformGCPVertex AIPrometheusGrafanaELK stackPythonBashMicroservices

Company Brief

HD Supply

Industry: Wholesale & Distribution

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Unicorn (USD 1B+)

Funding: Private Equity Backed

Headquarters: Atlanta, United States

Website LinkedIn