Position : - Machine Learning - Operations LEAD (ML) / MLOps Lead

Looking for Immediate Joiner / Within 20 days Max

Recruiter - Ms. Bhavani K    |  91-   82480 95114  |  Email  :-  bhavani@hashtagglobal.org

Roles and Responsibilities

• Ensure reliability and cost saving. Scale the proof of concept product to enterprise grade application with all the required components for reliability, scalability, monitoring and security.
• Suggest and implement the best practices from Software engineering to ML workflow to ensure
• CI/CD, reproducibility and quick delivery cycle.
• Lead and drive the deployment of ML models, life cycle management and monitoring of Machine Learning(ML) and Deep Learning (DL) models in in all stages leading to production
• Be a subject matter expert on DevOps practices, CI/CD and Configuration Management with
• assigned engineering team
• Automate and streamline ML operations and processes.
• Build and maintain tools for deployment, monitoring, and operations. Also troubleshoot and
• resolve issues in development, testing, and production environments
• Operate and maintain systems supporting the provisioning of new clients, applications, and
• features
• Work to improve Data scientist and Data engineer productivity and delivery speed by enabling
• them to be more self-sufficient with automated operational processes.
• Successfully devise and implement strategies to ensure ML heavy systems operate with high
• accuracy in Production and adapt to discovered needs.
• Collaborate with Data Scientists, Data Engineers, ML Engineers, cloud platform and application engineers to create and implement cloud policies and governance for ML/DL model life cycle

Desired Candidate Profile

.

• 8 to 10 years of industry experience working in Software Engineering, DevOps or Data
• Engineering with Data Science and MLOps experience.
• Strong DevOps, Data Engineering and Client background with AWS Experience with one or more of MLOps tools: ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC) etc.
• Experience in Distributed computing, Data pipelines, and AI/Client.
• Review and influence the engineering design, architecture and technology stack across multiple products
• Experience in Azure ML, Data Bricks, and Azure Kubernetes service.
• Extensive experience with Unix/AIX/Linux environments
• Experience with automation servers such as Jenkins, CloudBees, Travis, GitHub actions
• Experience with logging tools such as Splunk, ElasticSearch, Kibana, Logstash
• Familiarity with setting up Hyperparameter Tuning tools like optuna/ kubeflow/AWS Sagemaker or similar
• Familiarity with setting up model and experiment Versioning technologies like
• MLFLow/Kubeflow/AWS Sagemaker or similar

CONTACT FOR Information

Bhavani K    |    Recruitment Specialist  |    Mobile  :  91-   82480 95114  |  Email  :-  bhavani@hashtagglobal.org