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Module Lead - Gen AI / Machine Learning Engineer @ WinWire

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 Module Lead - Gen AI / Machine Learning Engineer

Job Description

Role & responsibilities

We are seeking an experienced and technically strong Machine Learning Engineer to design, implement, and operationalize ML models across Google Cloud Platform (GCP) and Microsoft Azure. The ideal candidate will have a robust foundation in machine learning algorithms, MLOps practices, and experience deploying models into scalable cloud environments.


Responsibilities:

  • Design, develop, and deploy machine learning solutions for use cases in prediction, classification, recommendation, NLP, and time series forecasting.
  • Translate data science prototypes into production-grade, scalable models and pipelines.
  • Implement and manage end-to-end ML pipelines using:
  • Azure ML (Designer, SDK, Pipelines), Data Factory, and Azure Databricks
  • Vertex AI (Pipelines, Workbench), BigQuery ML, and Dataflow
  • Build and maintain robust MLOps workflows for versioning, retraining, monitoring, and CI/CD using tools like MLflow, Azure DevOps, and GCP Cloud Build.
  • Optimize model performance and inference using techniques like hyperparameter tuning, feature selection, model ensembling, and model distillation.
  • Use and maintain model registries, feature stores, and ensure reproducibility and governance.
  • Collaborate with cloud architects, and software engineers to deliver ML-based solutions.
  • Maintain and monitor model performance in production using Azure Monitor, Prometheus, Vertex AI Model Monitoring, etc.
  • Document ML workflows, APIs, and system design for reusability and scalability.

Primary Skills required (Must Have Expereince):

  • 5 -7 years of experience in machine learning engineering or applied ML roles.
  • Advanced proficiency in Python, with strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch.
  • Solid understanding of core ML concepts: supervised/unsupervised learning, cross-validation, bias-variance tradeoff, evaluation metrics (ROC-AUC, F1, MSE, etc.).
  • Hands-on experience deploying ML models using:
  • Azure ML (Endpoints, SDK), AKS, ACI
  • Vertex AI (Endpoints, Workbench), Cloud Run, GKE
  • Familiarity with cloud-native tools for storage, compute, and orchestration:
  • Azure Blob Storage, ADLS Gen2, Azure Functions
  • GCP Storage, BigQuery, Cloud Functions
  • Experience with containerization and orchestration (Docker, Kubernetes, Helm).
  • Strong understanding of CI/CD for ML, model testing, reproducibility, and rollback strategies.
  • Experience implementing drift detection, model explainability (SHAP, LIME), and responsible AI practices.

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Machine Learning Engineer
Employement Type: Full time

Contact Details:

Company: WinWire
Location(s): Hyderabad

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Keyskills:   Azure ML evaluation metrics Scikit-learn Machine Learning NumPy bias-variance tradeoff PyTorch XGBoost LightGBM cross validation Pandas TensorFlow

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WinWire

Winwire Technologies India Pvt. Ltd. About WinWire: WinWire Technologies is a specialized IT solutions company focused on making information actionable for the enterprises. We help business and technology leaders achieve an 'on-the-move' business environment by leveraging pre-built collaborat...