HD Supply

2 months ago

Lead Software Engineer - ML

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Reposted: first listed 4 days ago

Job Summary

Lead end-to-end Machine Learning solution design and delivery, including feature pipelines, model architecture, evaluation, and production deployment. Oversee scalable training/inference/monitoring pipelines with retraining and bias/validation best practices. Provide technical leadership to ML engineers, partner with MLOps and platform teams, and ensure production readiness via logging, observability, model/version tracking, and drift monitoring. Work with cloud-native ML platforms such as GCP Vertex AI and Azure ML.

Location: Chennai

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead end-to-end ML solution design, covering feature pipelines, model architecture, evaluation frameworks, and production deployment strategies.
•Oversee scalable ML pipelines for training, inference, monitoring, and automated retraining.
•Drive best practices for model validation, bias analysis, experiments, hyperparameter tuning, and cross-validation.
•Provide technical leadership by coaching and mentoring ML engineers and junior team members on ML engineering patterns and coding standards.
•Ensure production readiness through logging, observability, model/version tracking, and monitoring of drift or degradation.

Key Requirements

•Bachelor’s or master’s degree in computer science, information systems, engineering, or a related field.
•7–10 years delivering ML systems or data-driven applications, including 2–3 years in a technical leadership or mentoring capacity.
•Hands-on experience designing, deploying, and operationalizing ML models (e.g., forecasting, recommendations, classification, NLP) using cloud-native ML platforms such as GCP Vertex AI or Azure ML.
•Advanced proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch), plus distributed processing (Spark, Beam).
•Experience with CI/CD for ML (MLOps), including automated retraining, model monitoring, and deployment workflows; plus data warehouses/analytics such as Snowflake and Tableau.

Experience:7-10 years

Education:Bachelor's

Skills:Technical leadershipMentoringCoding disciplineCross-functional collaborationProblem troubleshooting

Certifications:TensorFlowDatabricksAWS MLGCP MLAzure ML

Tech Stack:PythonScikit-learnTensorFlowPyTorchSparkBeamGCP Vertex AIAzure MLAWSDatabricksGCPAzureCI/CDMLOpsSnowflakeTableauKubernetesDockerServerlessRAG

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

2 months ago

Lead Software Engineer - ML

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Reposted: first listed 4 days ago

Job Summary

Location: Chennai

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead end-to-end ML solution design, covering feature pipelines, model architecture, evaluation frameworks, and production deployment strategies.
•Oversee scalable ML pipelines for training, inference, monitoring, and automated retraining.
•Drive best practices for model validation, bias analysis, experiments, hyperparameter tuning, and cross-validation.
•Provide technical leadership by coaching and mentoring ML engineers and junior team members on ML engineering patterns and coding standards.
•Ensure production readiness through logging, observability, model/version tracking, and monitoring of drift or degradation.

Key Requirements

•Bachelor’s or master’s degree in computer science, information systems, engineering, or a related field.
•7–10 years delivering ML systems or data-driven applications, including 2–3 years in a technical leadership or mentoring capacity.
•Hands-on experience designing, deploying, and operationalizing ML models (e.g., forecasting, recommendations, classification, NLP) using cloud-native ML platforms such as GCP Vertex AI or Azure ML.
•Advanced proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch), plus distributed processing (Spark, Beam).
•Experience with CI/CD for ML (MLOps), including automated retraining, model monitoring, and deployment workflows; plus data warehouses/analytics such as Snowflake and Tableau.

Experience:7-10 years

Education:Bachelor's

Skills:Technical leadershipMentoringCoding disciplineCross-functional collaborationProblem troubleshooting

Certifications:TensorFlowDatabricksAWS MLGCP MLAzure ML

Tech Stack:PythonScikit-learnTensorFlowPyTorchSparkBeamGCP Vertex AIAzure MLAWSDatabricksGCPAzureCI/CDMLOpsSnowflakeTableauKubernetesDockerServerlessRAG

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