| Immediate opening for ML Ops Engineer at Pennsylvania Remote at Remote, Remote, USA |
| Email: [email protected] |
| From: kranthi kumar, USG [email protected] Reply to: [email protected] Hi, Greetings!! We have an immediate opening for ML Ops Engineer at Pennsylvania Remote. Please go through the requirement and reply with your updated profile, contact details, and your availability if you would be interested in it. Position: ML Ops Engineer Location: Pennsylvania Remote Duration:6-12 Months 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. 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 Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology golang |
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| Fri Feb 02 03:00:00 UTC 2024 |