CyberTec
Client Ops Engineer at
Pennsylvania - EST/CST - Candidates only - 3-4 day need to be onsite in a month.
Summary: We are seeking a highly skilled and experienced MLOps Engineer to join our team in USA. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, working closely with the Generative AI Full Stack Architect . Your expertise in automating and streamlining the Client lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models in production. Responsibilities: Design, develop, and implement MLOps pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring. Automate Client tasks across the model lifecycle, leveraging tools like GitOps, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes). Develop and maintain robust monitoring and alerting systems for generative AI models in production, ensuring proactive identification and resolution of issues. Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization. Manage and maintain cloud infrastructure (e.g., AWS, GCP, Azure) for Client workloads, ensuring cost-efficiency and scalability. Stay up-to-date on the latest advancements in MLOps and incorporate them into our platform and processes. Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models. Qualifications:
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience. 8+ years of experience in MLOps or related areas, such as DevOps, data engineering, or Client infrastructure. Proven experience in automating Client pipelines with tools like MLflow, Kubeflow, Airflow, etc. Expertise in cloud platforms (e.g., AWS, Azure) for Client workloads. Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for Client systems (e.g., Prometheus, Grafana). Excellent communication, collaboration, and problem-solving skills. Ability to work independently and as part of a team. Passion for Generative AI and its potential to revolutionize various industries. Band 4C:
Senior individual contributor with significant expertise and leadership experience. Manages complex projects and initiatives with independent decision-making authority. Provides technical guidance and mentoring to junior team members. Has a proven track record of success in delivering impactful results.
Pennsylvania - EST/CST - Candidates only - 3-4 day need to be onsite in a month.
Summary: We are seeking a highly skilled and experienced MLOps Engineer to join our team in USA. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, working closely with the Generative AI Full Stack Architect . Your expertise in automating and streamlining the Client lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models in production. Responsibilities: Design, develop, and implement MLOps pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring. Automate Client tasks across the model lifecycle, leveraging tools like GitOps, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes). Develop and maintain robust monitoring and alerting systems for generative AI models in production, ensuring proactive identification and resolution of issues. Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization. Manage and maintain cloud infrastructure (e.g., AWS, GCP, Azure) for Client workloads, ensuring cost-efficiency and scalability. Stay up-to-date on the latest advancements in MLOps and incorporate them into our platform and processes. Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models. Qualifications:
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience. 8+ years of experience in MLOps or related areas, such as DevOps, data engineering, or Client infrastructure. Proven experience in automating Client pipelines with tools like MLflow, Kubeflow, Airflow, etc. Expertise in cloud platforms (e.g., AWS, Azure) for Client workloads. Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for Client systems (e.g., Prometheus, Grafana). Excellent communication, collaboration, and problem-solving skills. Ability to work independently and as part of a team. Passion for Generative AI and its potential to revolutionize various industries. Band 4C:
Senior individual contributor with significant expertise and leadership experience. Manages complex projects and initiatives with independent decision-making authority. Provides technical guidance and mentoring to junior team members. Has a proven track record of success in delivering impactful results.