Java Programming, Python Programming, DevOps, Git, Azure, AWS, Aartificial intelligence, Machine learning techniques, Data science techniques, Employee life cycle, Jenkins, PyTorch, TensorFlow, Kubernetes-K8s, Continuous Integration & Continuous Delivery - CI/CD, Google Cloud Platform (GCP), Ansible, Amazon Elastic Compute Cloud-EC2, Shell Scripting language, Puppet, Caffe, Lambda, Amazon Simple Storage Service (S3), Software Development, Infrastructure-as-code-IaC, GitLab
We are seeking an experienced Senior MLOps Engineer with Kubernetes background to join our dynamic team. The Engineer will be responsible for bridging the gap between development, operations, and data science teams to ensure smooth deployment and operation of machine learning models in production environments. The ideal candidate will have a strong background in managing Kubernetes clusters at scale, deploying, maintaining and optimizing infrastructure for performance and reliability. Responsibilities include designing, implementing, and supporting Kubernetes clusters, automating deployment processes, monitoring system health, troubleshooting issues, and collaborating with cross-functional teams to ensure the smooth operation of our cloud-native infrastructure. The candidate should possess excellent communication skills, a proactive attitude, and a passion for staying updated with emerging technologies in the Kubernetes ecosystem. This role offers an exciting opportunity to contribute to the growth and success of our organization in a rapidly evolving cloud computing landscape.
Responsibilities
Requirements
Good To Have
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