Machine Learning Engineer

Hi,

🔍 We're Hiring!

I'm excited to share that we're looking for Machine Learning Engineer to join our team at ITC Infotech.

Below is the JD for your reference.

Job Title: Machine Learning Engineer

Location: Mumbai, Pune, Bangalore, Hyderabad, Gurgaon, Kolkata (Hybrid, based on project needs)

Type: Full-time

Experience Level: 12 to 18 Years

Key Responsibilities

·Model Development: Build, train, and optimize ML models using frameworks like Scikit-learn, PyTorch, TensorFlow.

·Data Engineering: Preprocess and manage large datasets using Azure Data Lake, Azure Synapse, Databricks, SQL, Pandas, Spark.

·Data Pipeline Management: Build and maintain scalable ETL workflows with Azure Databricks, Synapse, and Data Lake Storage.

·Deployment & Integration: Operationalize ML models into production using Azure ML, AKS, Docker, and Kubernetes.

·Implement and maintain CI/CD pipelines for model training, testing, and deployment (using GitHub Actions).

·Manage Databricks clusters, pipelines, and administrative configurations (including Unity Catalog and workspace permissions).

·Use Azure ML services to manage model registry, batch endpoints, and online deployment.

·Collaborate with platform, security, and cloud teams to ensure best practices across environments.

·Experimentation & tuning: Run HyperDrive jobs for hyperparameter search; apply cross‑validation and early stopping to improve generalization.

·Feature management: Build and serve features via a Feature Store to ensure consistency across training and inference.

·Testing & quality gates: Implement data and model tests (pytest, Great Expectations) and enforce validation gates in pipelines.

·Performance optimization: Use GPU/accelerator compute, distributed training, and export models to ONNX/TorchScript for low‑latency inference.

·Inference strategies: Design batch and real‑time endpoints, with A/B or shadow deployments and canary releases for safe production rollout.

·Responsible AI & explainability: Integrate SHAP for explanations and monitor fairness/bias metrics.

·Security & compliance: Enforce RBAC, Managed Identities, Key Vault secrets, VNet/Private Link, and encryption standards.

·Cost & scalability: Monitor compute/storage costs, enable autoscaling, and optimize resource utilization.

If you're interested or know someone who might be a great fit, please reach out or apply