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Capgemini
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Automation Engineer

Automation Engineer

Capgemini

6 - 10 years

0 Lacs

karnataka

Posted:18 hours ago| Platform: Shine logo

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Skills Required

aws azure gcp teamcity jenkins airflow docker kubernetes openshift python go ruby bash linux english communication skills teamwork mlops cicd kubeflow mlflow datarobot scikitlearn keras pytorch tensorflow

Work Mode

On-site

Job Type

Full Time

Job Description

At Capgemini Engineering, the world leader in engineering services, a global team of engineers, scientists, and architects come together to assist innovative companies in unleashing their potential. Our digital and software technology experts provide unique R&D and engineering services across all industries, from autonomous cars to life-saving robots. A career at Capgemini Engineering is full of opportunities where you can make a difference and where no two days are the same. As a member of our team, your responsibilities will include designing, developing, and implementing MLOps pipelines for the continuous deployment and integration of machine learning models. You will collaborate with data scientists and engineers to understand model requirements and optimize deployment processes. It will be your task to take offline models data scientists build and transform them into a real machine learning production system. Automation of the training, testing, and deployment processes for machine learning models will be a key aspect of your role. Continuously monitoring and maintaining models in production to ensure optimal performance, accuracy, and reliability will be essential. You will be expected to implement best practices for version control, model reproducibility, and governance while optimizing machine learning pipelines for scalability, efficiency, and cost-effectiveness. Troubleshooting and resolving issues related to model deployment and performance will also fall under your responsibilities. Ensuring compliance with security and data privacy standards in all MLOps activities is crucial. Staying up-to-date with the latest MLOps tools, technologies, and trends will be necessary to excel in this role. You will provide support and guidance to other team members on MLOps practices and communicate effectively with a team of data scientists, data engineers, and architects. Documenting processes accurately will be part of your routine tasks. The ideal candidate will have experience in designing and implementing MLOps pipelines on platforms like AWS, Azure, or GCP. Hands-on experience in building CI/CD pipelines orchestration using tools such as TeamCity, Jenkins, Airflow, or similar is required. Familiarity with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow, as well as experience with Docker and Kubernetes, OpenShift is essential. Proficiency in programming languages like Python, Go, Ruby, or Bash is expected, along with a good understanding of Linux and knowledge of frameworks like scikit-learn, Keras, PyTorch, Tensorflow, etc. The ability to comprehend tools used by data scientists and experience with software development and test automation will be advantageous. Fluent English, good communication skills, and the ability to work effectively in a team are essential qualities for this role.,

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Automation Engineer