LTIMindtree | MLOPS

6 days ago

bangalore, India LTIMindtree Full time
LTIMindtree is looking for MLOPS role:
Experience- 5 to 8 Years
Job Location- Bangalore
We seek a Senior ML Ops Engineer to play a critical role in operationalizing machine learning workflows that drive dynamic pricing and personalized consumer experiences This position focuses on building robust ML infrastructure and frameworks including drift detection model calibration versioning and reinforcement learning orchestration The ideal candidate will bring expertise in Databricks Unity Catalog and feature stores and a deep understanding of Git workflows Databricks workflows and automated ML training pipelines
Key Responsibilities
ML Infrastructure Development Build and maintain scalable ML infrastructure on Databricks leveraging Unity Catalog and feature stores to support model development and deployment
Drift Detection Frameworks Design and implement frameworks for detecting data and model drift ensuring continuous monitoring and high reliability of ML models in production
Model Calibration Versioning Develop model calibration frameworks and establish versioning practices to maintain transparency and reproducibility across the ML lifecycle
LowLatency Orchestration Design and optimize reinforcement learning RL orchestration pipelines including Contextual Bandits for realtime execution in lowlatency environments
Automated Training Pipelines Create automated frameworks for training retraining and validating ML models enabling efficient experimentation and deployment
CICD for ML Implement CICD best practices to streamline the deployment and monitoring of ML models integrating with Databricks workflows and Gitbased version control systems
Collaboration Work closely with ML Scientists to ship deploy and maintain models
Monitoring Optimization Build tools for model performance monitoring operational analytics and drift mitigation ensuring reliable operation in production environments
Qualifications
7 years in MLOps ML Engineering or related roles focusing on deploying and managing ML workflows in production environments Handson experience building drift detection systems model calibration frameworks and robust monitoring tools for ML pipelines
Proficient in using Databricks Apace Spark ML Flow Unity Catalog and feature stores
Expertise in deploying and orchestrating lowlatency ML models including reinforcement learning solutions like Contextual Bandits and Qlearning
Experience designing automated training pipelines for ML models focussing on efficiency
Strong knowledge of Git workflows CICD practices and tools like GitLab or similar
Proficiency in Python SQL and big data processing tools like Spark
Familiarity with ML lifecycle tools such as MLflow Kubeflow and Airflow
Strong understanding of model performance monitoring drift detection and retraining workflows
If interested please share resume on

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