181 Automation Scripting Jobs

DevOps Machine Learning Role Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues re...

Responsibilities Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes Automate the training, testing and deployment processes for machine learning models Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability Implement best practices for version control, model reproducibility and governance Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness Troubleshoot and resolve issues related to model deployment and performance Ensure c...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. 4. Automate the training, testing and deployment processes for machine learning models Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. 6. 7. 8. 9. Implement best practices for version control, model reproducibility and governance Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness Troubleshoot and resolve issues related to model deployme...

MLOps Role Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model dep...

Responsibilities 1. Design, Develop, And Implement Mlops Pipelines For The Continuous Deployment And Integration Of Machine Learning Models 2. Collaborate With Data Scientists And Engineers To Understand Model Requirements And Optimize Deployment Processes 3. Automate The Training, Testing And Deployment Processes For Machine Learning Models 4. Continuously Monitor And Maintain Models In Production, Ensuring Optimal Performance, Accuracy And Reliability 5. Implement Best Practices For Version Control, Model Reproducibility And Governance 6. Optimize Machine Learning Pipelines For Scalability, Efficiency And Cost-Effectiveness 7. Troubleshoot And Resolve Issues Related To Model Deployment And...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

JD- Cloud Infrastructure Maintain scalable data submission systems Platform-AWS Implement, monitor, and optimize data submission infrastructure in AWS. Ensure cloud solutions are scalable, cost-effective, and compliant with best practices. Collaborate with security and networking teams to safeguard data assets. Provide automation for provisioning and managing cloud resources. Experience in monitoring tools Datadog, Splunk, ELK JD- DevOps Practices Manage CI/CD pipelines & deployment Platform- Jenkins, GitHub Actions GitHub Actions, CI/CD pipeline design, automation scripting, version control (Git)

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 4. Implement best practices for version control, model reproducibility and governance Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 5. Troubleshoot and resolve issues related to model deployment and perfo...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

MLOps Role Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model dep...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

MLOps Role Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model dep...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

MLOps Role Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model dep...

As a Software Engineer Lead at UnitedHealth Group, you will play a crucial role in building cloud-based applications, especially on Azure, to ensure seamless integration and connectivity of resources. Your primary responsibilities will include providing technical solutions, analyzing current systems for potential flaws in cloud security, uploading business information to cloud platforms, and increasing cloud storage capacity. You will also work with stakeholders to understand system modifications, troubleshoot cloud application failure or security flaws, and automate specific system operations for enhanced efficiency. Additionally, you will be responsible for testing designs, identifying the...

Join us in helping leading Consumer Products and Retail Services (CPRS) organizations unlock the value of technology and drive scalable, sustainable growth. Your Role As a Platform Tester , you will be responsible for validating embedded systems and mobile platforms to ensure high-quality performance and reliability. You’ll work closely with development teams to design and execute test cases, identify issues, and contribute to improving product stability and user experience. In this role, you will: Perform functional and system-level testing on embedded platforms and mobile handsets. Design, build, and execute test cases on target devices to validate features and performance. Collaborate wit...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

Responsibilities 1. Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models 2. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes 3. Automate the training, testing and deployment processes for machine learning models 4. Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability 5. Implement best practices for version control, model reproducibility and governance 6. Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness 7. Troubleshoot and resolve issues related to model deployment and...

About The Role Project Role : Application Tech Support Practitioner Project Role Description : Act as the ongoing interface between the client and the system or application. Dedicated to quality, using exceptional communication skills to keep our world class systems running. Can accurately define a client issue and can interpret and design a resolution based on deep product knowledge. Must have skills : Infrastructure Automation Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :We are seeking a highly motivated and technically skilled GenAI & Prompt Engineering Specialist to join our Automation & Asset Deve...

As an Automation Engineer at the company, your primary role will be to automate all manual cases of Firewall and Hotspot Gateway Software. You will be responsible for raising bugs and coordinating with developers to ensure timely resolutions. It is expected that you will independently assume ownership of your work, demonstrating a high level of responsibility and initiative. Key Responsibilities: - Automate all manual cases of Firewall and Hotspot Gateway Software - Raise bugs and associate with developers to facilitate resolutions - Independently assume ownership of assigned work Qualifications Required: - Hands-on experience in Automation scripting and tools, Software Testing, Selenium - P...

As a Senior QA Engineer / QA Lead at our Pune location, you will have the opportunity to work with our dynamic team while servicing some of the top fortune 100 international technology companies. Your role will entail the following responsibilities: - Excellent communication skills to effectively handle any issue, requirement discussions, and daily stand-up calls with clients. - Ability to manage deadlines and adapt to unexpected changes in expectations or requirements. - Proficiency in creating test cases, test scenarios, and requirement documents essential for project execution and QA operations. - Experience in Manual Testing, API Testing (using tools like Postman), Integration Testing, a...