Manager - Automation

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Skills you'll use

What you'll do

• Key Performance Indicators (KPIs)
• AI & ML Development
• Build and deploy models using supervised, unsupervised, and reinforcement learning techniques for use cases such as forecasting, predictive scenarios, dynamic pricing & recommendation engines, and anomaly detection, with exposure to broad enterprise functions and business
• Lead development of models, NLP classifiers, and GenAI-enhanced prediction engines.
• Design and integrate LLM-based features such as prompt pipelines, fine-tuned models, and inference architecture using Gemini, Azure OpenAI, LLama etc.
• Program Plan Vs Actuals
• End-to-End Solutioning
• Translate business problems into robust data science pipelines with emphasis on accuracy, explainability, and scalability.
• • Own the full ML lifecycle — from data ingestion and feature engineering to model training, evaluation, deployment, retraining, and drift management.
• Program Plan Vs Actuals

Who can apply

• Engineering degree
• Masters preferable
• RELEVANT EXPERIENCE
• 5 - 8years of hands-on experience in machine learning, AI engineering, or data science, including deploying models at scale.
• Strong programming and modelling skills in some like Python, SQL, and ML frameworks like scikit-learn, TensorFlow, XGBoost, PyTorch.
• Demonstrated ability to build models using supervised, unsupervised, and reinforcement learning techniques to solve complex business problems.
• Technical & Platform Skills
• Proven experience with cloud-native ML tools: AWS SageMaker, Azure ML Studio, Google AI
• Familiarity with DevOps and orchestration tools: Docker, Git, Step Functions, Lambda,Google AI or similar
• Comfort working with BI/reporting layers, testing, and model performance dashboards.

About GMR Group

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