| Immediate Hiring ML Ops Engineer--Remote at Remote, Remote, USA |
| Email: [email protected] |
| From: Shiva Manish, Talentgroups [email protected] Reply to: [email protected] This is Shiva Manish I have an excellent job opportunity with one of our premier clients. Since it is an urgent business requirement your prompt response is appreciated Job title: ML Ops Engineer Location: Pennsylvania US - WFH Virtual 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 ML 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 ML 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 ML 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 we seek in you: Minimum 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 ML infrastructure. Proven experience in automating ML pipelines with tools like MLflow, Kubeflow, Airflow, etc. Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads. Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes. Familiarity with monitoring and alerting tools for ML 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. Preferred Qualifications/ skills Experience with Agile methodology delivery and hands-on leadership role Proven Track record of continued and recent hands-on experience as full stack architecture. Talent Group is excited to announce a streamlined vendor management process through our partnership with iLabor, a state-of-the-art vendor management technology. This integration with our ATS platform aims to enhance efficiency, compliance, and speed in candidate sourcing and placement. As part of our Preferred Vendor Program, you'll receive priority access to all job requirements, real-time updates on candidate progress, and instant receipt of all orders. This move eliminates the need for multiple communications and offers a unified, efficient approach to our business transactions. By leveraging this powerful partnership, we aim to redefine how we work together and create a seamless experience for both vendors and clients. Our focus is on empowering you with the tools and resources necessary to thrive in today's competitive market. Thanks, SHIVAMANISH BAIRAGONI [email protected] Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology |
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| Thu Feb 22 00:25:00 UTC 2024 |