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RARR Technologies

Mlops lead Engineer

8-13 Years
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Job Description

  • Responsible for building and maintaining robust machine learning pipelines ensuring efficient model deployment monitoring and lifecycle management within a cloud based environment
  • Extensive expertise in MLOps specifically with Google Cloud Platform GCP and Vertex AI and a deep understanding of model performance drift detection and GPU accelerators
  • Build and maintain scalable MLOps pipelines in GCP Vertex AI for endtoend machine learning workflows
  • Manage the full MLOps lifecycle from data preprocessing model training and deployment to model monitoring and drift detection
  • Implement realtime model monitoring and drift detection to ensure optimal model performance over time
  • Building and execution of CICD containerization and orchestration tools Handson experience in Jenkins GitHub Pipelines Docker Kubernetes and OpenShift
  • Optimize model training and inference processes using GPU accelerators and CUDA
  • Collaborate with cross functional teams to automate and streamline machine learning model deployment and monitoring
  • Utilize Python 310 with libraries such as pandas NumPy and TensorFlow to handle data processing and model development
  • Set up infrastructure for continuous training testing and deployment of machine learning models
  • Ensure scalability security and high availability in all machine learning operations by implementing best practices in MLOps.

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Open to candidates from:
Indian

About Company

At RARR Technologies Pvt. Ltd., we believe in the power of collaboration and open communication. Our collaborative approach enables us to deeply understand our clients requirements, allowing us to craft software products that are not only technically superior but also align perfectly with their business goals. By combining our expertise with a meticulous attention to detail, we ensure that every line of code we write contributes to the creation of robust, scalable, and future-proof digital solutions that stand the test of time.

Job ID: 112902843