AI ML Engineer

About The Opportunity A fast-moving, innovation-driven organization in the Enterprise AI & Machine Learning sector, we build and deploy scalable ML-powered solutions that drive automation, predictive analytics, and intelligent decision-making across industries. Our ML Engineers work at the intersection of algorithmic rigor and real-world product impacttransforming raw data into high-accuracy, production-grade models used by thousands of users daily. Role & Responsibilities Design, train, and deploy machine learning modelsclassification, regression, clusteringfor live business use cases across domains.Build and optimize end-to-end ML pipelines: data ingestion feature engineering model training inference monitoring.Collaborate with data engineers to integrate ML models into scalable cloud infrastructure (AWS/GCP/Azure).Implement and evaluate model performance using metrics such as precision, recall, F1-score, AUC-ROC, and business-specific KPIs.Develop model explainability and fairness tooling to support auditability and stakeholder trust.Automate retraining, drift detection, and model versioning using CI/CD workflows and MLOps best practices. Skills & Qualifications Must-Have PythonScikit-learnPandasNumPyTensorFlowPyTorchMLflowGit Preferred Experience with Hugging Face TransformersFamiliarity with AWS SageMaker or GCP Vertex AIKnowledge of XGBoost / LightGBM / CatBoost Benefits & Culture Highlights Opportunity to work on high-impact, customer-facing AI/ML products with measurable ROI.Collaborative, feedback-rich environment with mentorship from senior ML architects.On-site culture with flexible core hours, team lunches, and quarterly hackathons. Skills: learning,ml,machine learning,data,aws About The Opportunity A fast-moving, innovation-driven organization in the Enterprise AI & Machine Learning sector, we build and deploy scalable ML-powered solutions that drive automation, predictive analytics, and intelligent decision-making across industries. Our ML Engineers work at the intersection of algorithmic rigor and real-world product impacttransforming raw data into high-accuracy, production-grade models used by thousands of users daily. Role & Responsibilities Design, train, and deploy machine learning modelsclassification, regression, clusteringfor live business use cases across domains.Build and optimize end-to-end ML pipelines: data ingestion feature engineering model training inference monitoring.Collaborate with data engineers to integrate ML models into scalable cloud infrastructure (AWS/GCP/Azure).Implement and evaluate model performance using metrics such as precision, recall, F1-score, AUC-ROC, and business-specific KPIs.Develop model explainability and fairness tooling to support auditability and stakeholder trust.Automate retraining, drift detection, and model versioning using CI/CD workflows and MLOps best practices. Skills & Qualifications Must-Have PythonScikit-learnPandasNumPyTensorFlowPyTorchMLflowGit Preferred Experience with Hugging Face TransformersFamiliarity with AWS SageMaker or GCP Vertex AIKnowledge of XGBoost / LightGBM / CatBoost Benefits & Culture Highlights Opportunity to work on high-impact, customer-facing AI/ML products with measurable ROI.Collaborative, feedback-rich environment with mentorship from senior ML architects.On-site culture with flexible core hours, team lunches, and quarterly hackathons. Skills: learning,ml,machine learning,data,aws