Senior ML Analyst -(End-to-End Model Deployment)

Spectral Consultants is #Hiring | Sr. Analyst Machine Learning (End-to-End Model Deployment) Location: Bangalore Experience: 3 4.5 Years What You'll Do Build, train, fine-tune, validate, and deploy machine learning models Develop production-ready ML solutions using Python Work with algorithms such as Regression, Decision Trees, Random Forest, XGBoost, Neural Networks, CNNs, and Transformers Deploy and monitor models using MLOps best practices Build and support automated ML pipelines in cloud environments (Azure/AWS/GCP) Collaborate with stakeholders to solve real-world business problems Required Skills Python & SQLMachine Learning & Deep LearningModel Training & Fine-TuningEnd-to-End Model DeploymentMLOps (MLflow, Git/GitHub, CI/CD)Cloud Platforms (Azure, AWS, or GCP)Spark/PySpark (preferred) We're Looking For Candidates Who Have hands-on experience building and deploying ML models in production Can explain algorithm selection, model training, validation, and optimization Have worked across the complete machine learning lifecycle Possess strong problem-solving and communication skills Spectral Consultants is #Hiring | Sr. Analyst Machine Learning (End-to-End Model Deployment) Location: Bangalore Experience: 3 4.5 Years What You'll Do Build, train, fine-tune, validate, and deploy machine learning models Develop production-ready ML solutions using Python Work with algorithms such as Regression, Decision Trees, Random Forest, XGBoost, Neural Networks, CNNs, and Transformers Deploy and monitor models using MLOps best practices Build and support automated ML pipelines in cloud environments (Azure/AWS/GCP) Collaborate with stakeholders to solve real-world business problems Required Skills Python & SQLMachine Learning & Deep LearningModel Training & Fine-TuningEnd-to-End Model DeploymentMLOps (MLflow, Git/GitHub, CI/CD)Cloud Platforms (Azure, AWS, or GCP)Spark/PySpark (preferred) We're Looking For Candidates Who Have hands-on experience building and deploying ML models in production Can explain algorithm selection, model training, validation, and optimization Have worked across the complete machine learning lifecycle Possess strong problem-solving and communication skills