| Remote but 3-4 Days / Month Onsite (PA) || MLOps Engineer || Long Term Contract at Remote, Remote, USA |
| Email: [email protected] |
| Only for H1B / H4 EAD || Only for EST and CST Candidates Please mention Visa status and Current location while sharing resume To get fast response mention if anyone is having Any Implementation Partner Experience,. 10+ years Min || $80/hr Neg. Job Title- MLOps Engineer Location: Remote ( Pennsylvania - this role involves traveling to client location 3-4 days in a month, expenses incurred by the client) Candidate should be either in EST or CST time zone. ) Type: : long Term Contract Responsibilities: 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 Your sincerely , Ajay Sharma | Sr. Technical Recruiter. Net 2Source Inc. Fax: (201) 221-8131 | Email: [email protected] Global HQ Address: 270 Davidson Ave, Suite 704, Somerset, NJ 08873, USA Web: www.net2source.com | Social: | | Disclaimer: Information contained and transmitted by this E-MAIL including any attachment is proprietary to Net2Source (along with its subsidiaries and affiliates) and is intended solely for the addressee/s, and may contain information that is privileged, confidential or exempt from disclosure under applicable law. Access to this e-mail and/or to the attachment by anyone else is unauthorized. If this is a forwarded message, the content and the views expressed in this E-MAIL may not reflect those of N2S. If you are not the intended recipient, an agent of the intended recipient or a person responsible for delivering the information to the named recipient, you are notified that any use, distribution, transmission, printing, copying or dissemination of this information in any way or in any manner is strictly prohibited. If you are not the intended recipient of this mail kindly delete from your system and inform the sender with a copy to [email protected]. There is no guarantee that the integrity of this communication has been maintained and nor is this communication free of viruses, interceptions, or interference. The GDPR (General Data Protection Regulation) came into effect on May 25, 2018, we have your e-mail address in our database to keep you updated with news, updated and notifications. Please view our Data Privacy Policy for more information. -- Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology New Jersey |
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| Thu Feb 22 20:28:00 UTC 2024 |