4 Kubernetes Gke Jobs

As a highly skilled MLOps Engineer at UPS, you will design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). Your responsibilities will include automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. Your role will involve collaborating with technical teams and business stakeholders to develop cutting-edge machine learning systems that add value to the business. Responsibilities: - Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. - Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. - Troubleshooting and resolving problems, maintaining documentation, and managing model versions for audit and rollback. - Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. - Optimization of queries and pipelines. - Modernization of applications whenever required. Qualifications: - Expertise in programming languages like Python, SQL. - Solid understanding of best MLOps practices and concepts for deploying enterprise-level ML systems. - Understanding of Machine Learning concepts, models, and algorithms including traditional regression, clustering models, and neural networks (including deep learning, transformers, etc.). - Understanding of model evaluation metrics, model monitoring tools, and practices. - Experience with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. - Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. - Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. - Bachelor's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: - Experience in Azure MLOPS. - Familiarity with Cloud Billing. - Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. - Experience working in an Agile environment, understanding of Lean Agile principles. UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.,

As a Full-time GCP DevOps Engineer at our company, you will be responsible for leading a team and utilizing your expertise in Google Cloud Platform (GCP). With your GCP Professional Cloud Architect or DevOps Engineer certification, along with a minimum of 5 years of experience, you will play a key role in optimizing our cloud infrastructure. Your hands-on experience with various core GCP services such as Compute Engine, Cloud Storage, VPC, IAM, BigQuery, Cloud SQL, Cloud Functions, Operations Suite Terraform will be crucial in ensuring the efficiency and reliability of our systems. Additionally, your proficiency in CI/CD tools like Jenkins, GitLab CI/CD, Cloud Build will help streamline our development processes. You should have a strong background in containerization technologies including Docker, Kubernetes (GKE), Helm, and be adept at scripting using languages such as Python, Bash, or Go for automation purposes. Your familiarity with monitoring and observability tools like Prometheus, Grafana, Cloud Monitoring will allow you to maintain the health and performance of our infrastructure. Furthermore, your proven knowledge of cloud security, compliance, and cost optimization strategies will be essential in safeguarding our systems and maximizing cost-efficiency. Experience with API Gateway / Apigee, service mesh, and microservices architecture will be an added advantage in this role. If you are a detail-oriented individual with a passion for GCP DevOps and a track record of successful team leadership, we invite you to apply for this exciting opportunity in either Hyderabad or Indore.,

We are looking for a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). Your responsibilities will include automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will collaborate with technical teams to develop cutting-edge machine learning systems that drive business value. In this role, you will manage the deployment and maintenance of machine learning models in production environments, ensuring seamless integration with existing systems. You will monitor model performance using metrics such as accuracy, precision, recall, and F1 score, addressing issues like performance degradation, drift, or bias. Troubleshooting problems, maintaining documentation, and managing model versions for audit and rollback will be part of your routine tasks. Your duties will also involve analyzing monitoring data proactively to identify potential issues and providing regular performance reports to stakeholders. Additionally, you will focus on optimizing queries and pipelines, as well as modernizing applications when necessary. To qualify for this role, you should have expertise in programming languages like Python and SQL, along with a solid understanding of best MLOps practices for deploying enterprise-level ML systems. Familiarity with Machine Learning concepts, models, and algorithms, such as regression, clustering, and neural networks, including deep learning and transformers, is essential. Experience with GCP tools like BigQueryML, Vertex AI Pipelines, Model Versioning & Registry, Cloud Monitoring, and Kubernetes is preferred. Strong communication skills, both written and oral, are crucial, as you will be required to prepare detailed technical documentation for new and existing applications. You should demonstrate strong ownership and collaborative qualities in your domain, taking the initiative to identify and drive opportunities for improvement and process streamlining. A Bachelor's Degree in a quantitative field or equivalent job experience is required for this position. Experience in Azure MLOPS, familiarity with Cloud Billing, setting up or supporting NLP, Gen AI, LLM applications with MLOps features, and working in an Agile environment are considered bonus qualifications. If you are passionate about MLOps, have a knack for problem-solving, and enjoy working in a collaborative environment to deliver innovative machine learning solutions, we would like to hear from you.,

As a GCP DevOps Lead, you will be responsible for leading the architecture and infrastructure strategy using Google Cloud Platform (GCP). Your role will involve designing, implementing, and managing CI/CD pipelines, infrastructure as code, and deployment automation to ensure high availability, scalability, and performance of cloud environments. You will guide a team of DevOps engineers in daily operations and project execution, while also implementing and maintaining monitoring, logging, and alerting frameworks such as Stackdriver, Prometheus, and Grafana. Driving security best practices, collaborating with cross-functional teams, and optimizing cost, resource usage, and performance in GCP will be key aspects of your responsibilities. The ideal candidate should possess 7+ years of total experience in DevOps, Cloud, or Infrastructure roles, with at least 3 years of hands-on experience with Google Cloud Platform (GCP). Strong skills in CI/CD tools like Jenkins, GitLab CI/CD, or Cloud Build, along with proficiency in Docker and Kubernetes (GKE) are essential. Experience with Terraform, Ansible, or Deployment Manager, source control systems like Git and Bitbucket, scripting languages such as Python, Bash, or Go, and knowledge of networking components and monitoring tools are also required. Understanding DevSecOps practices and security compliance standards will be beneficial in this role.,