MLOps Engineer

Job Description:

• We are seeking an experienced MLOps Engineer to design, deploy, automate, and maintain scalable machine learning platforms and workflows.
• The ideal candidate will have hands-on experience managing the ML lifecycle, building CI/CD pipelines, working with cloud platforms, using containerization, and supporting model deployment.

Key Responsibilities:

• Own the successful delivery of MLOps solutions and services in client consulting environments.
• Define the key business problems to be solved; formulate high-level solution approaches; identify the data required to address those problems; develop, analyze, draw conclusions, and present findings to the client.
• Support clients with operationalization by providing metrics to track the performance of ML Models.
• Help the team with ML Pipelines from creation through execution.
• Assist the team in debugging issues related to pipeline failures.
• Review and implement requirements for operationalization of ML Models received from Data Scientists.
• Engage with business stakeholders by providing status updates on development progress and issue resolution.
• Set up standards related to coding pipelines and documentation.
• Conduct research on new topics, services, and enhancements in cloud technologies.

Technical Requirements:

• Machine Learning MLOps
• ML lifecycle management
• Model deployment and monitoring
• Feature stores and model registries
• Experiment tracking
• Tools Frameworks
• MLflow
• Kubeflow
• Airflow
• TensorFlow PyTorch Scikit learn
• Apache Spark preferred

Preferred Skills:

Technology->AI-AI Engineering->MLOps,Technology->AI-Data science->PYTHON - AI-Data Science